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 Arief Anshory Yusu f & Herminia Francisco Climate Change  V ulnerability Mapping for Southeast Asia Sida  

Climate Change Vulnerability Mapping for Southeast Asia

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Arief Anshory Yusuf amp Herminia Francisco

Climate Change

Vulnerability Mappingfor Southeast Asia

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Climate Change Vulnerability Mappingfor Southeast Asia

Arief Anshory Yusuf amp Herminia A Francisco

January 2009

Economy and Environment Program for Southeast Asia

Sida SWEDISH INTERNATIONAL DEVELOPMENT COOPERATION AGENCY

Canadian International

Development Agency

Agence Canadienne de

Deacuteveloppment International

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Comments should be sent to

Dr Arief Anshory Yusuf (email ariefyusuffeunpadacid) orDr Herminia Francisco (email hfranciscoidrcorgsg)

Economy and Environment Program for Southeast Asia (EEPSEA)22 Cross Street 02-55 South Bridge Court Singapore 048421 Tel 65 6438 7877 Fax 65 6438 4844httpwwweepseaorg

EEPSEA was established in May 1993 to support research and training in environmental and resourceeconomics Its objective is to enhance local capacity to undertake the economic analysis ofenvironmental problems and policies It uses a networking approach involving courses meetingstechnical support access to literature and opportunities for comparative research Member countries are Thailand Malaysia Indonesia the Philippines Vietnam Cambodia Lao PDR China and Papua New

Guinea

EEPSEA is supported by the International Development Research Centre (IDRC) the SwedishInternational Development Cooperation Agency (Sida) and the Canadian International Development Agency (CIDA)

EEPSEA publications are also available online at httpwwweepseaorg

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CKNOWLEDGEMENTS

We are sincerely grateful to the participants of the Climate Change Vulnerability Experts Consultation

Meeting in Bangkok in May 2008 Prof Rex Cruz Dr Khairulmaini Osman Salleh Dr Rizaldi Boer Ms

Rosa T Perez Mr Luong Quang Huy Mr Syamphone Sengchandala Mr Hoang Minh Hien Mr

Nathaniel C Bantayan Mr Heng Chan Thoeun Dr Suppakorn Chinvanno Dr Anond Snidvongs Dr

Bui Dung The and Dr Orapan Nabangchang for their invaluable inputs on this assessment We are also

deeply appreciative of Dr Richard Fuchs for his insightful suggestions on the conceptualization of this

study and for funding this project through IDRCs Regional Activity Funds We further thank Ms Ang

Cheng Hiang for the assisting in the production and Mr Megananda of the Center for Economics and

Development Studies (CEDS) Padjadjaran University for his excellent research assistance The authors

are fully responsible for any errors in this assessment

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TABLE OF CONTENTS

10 INTRODUCTION 1

20 OBJECTIVES 1

30 METHODOLOGY AND DATA 2

31 Vulnerability Assessment 3

32 Generating the Component Maps for the Vulnerability Assessment 4

321 Climate-related hazard maps 5

322 Human and ecological sensitivity maps 7

323 Adaptive capacity map 8

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP OFSOUTHEAST ASIA 10

50 CONCLUDING REMARKS 14

REFERENCES 14

APPENDICES 15

Appendix 1 Sources of Data 15

Appendix 2 Climate Hazard Maps of Southeast Asia 18

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003) 18

Appendix 2B Flood frequency (event per year from 1980-2001) 18

Appendix 2C Drought frequency (event per year from 1980-2000) 19

Appendix 2D Landslide exposure (2005) 19

Appendix 2E Sea level rise (5-m inundation zone) 20

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia 21

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard) 21

Appendix 3B List of vulnerable provincesdistricts (country standard) 24

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ABSTRACT

This paper provides information on the sub-national areas (regionsdistrictsprovinces) most vulnerable

to climate change impacts in Southeast Asia This assessment was carried out by overlaying climate hazard

maps sensitivity maps and adaptive capacity maps following the vulnerability assessment framework of

the United Nationsrsquo Inter-governmental Panel on Climate Change (IPCC) The study used data on the

spatial distribution of various climate-related hazards in 530 sub-national areas of Indonesia Thailand

Vietnam Lao PDR Cambodia Malaysia and the Philippines Based on this mapping assessment all the

regions of the Philippines the Mekong River Delta in Vietnam almost all the regions of Cambodia

North and East Lao PDR the Bangkok region of Thailand and West Sumatra South Sumatra West Java

and East Java of Indonesia are among the most vulnerable regions in Southeast Asia

Keywords climate change vulnerability Southeast Asia

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1

10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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2

30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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4

Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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6

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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7

322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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16

Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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17

Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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18

Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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19

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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20

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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21

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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22

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Climate Change Vulnerability Mappingfor Southeast Asia

Arief Anshory Yusuf amp Herminia A Francisco

January 2009

Economy and Environment Program for Southeast Asia

Sida SWEDISH INTERNATIONAL DEVELOPMENT COOPERATION AGENCY

Canadian International

Development Agency

Agence Canadienne de

Deacuteveloppment International

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Comments should be sent to

Dr Arief Anshory Yusuf (email ariefyusuffeunpadacid) orDr Herminia Francisco (email hfranciscoidrcorgsg)

Economy and Environment Program for Southeast Asia (EEPSEA)22 Cross Street 02-55 South Bridge Court Singapore 048421 Tel 65 6438 7877 Fax 65 6438 4844httpwwweepseaorg

EEPSEA was established in May 1993 to support research and training in environmental and resourceeconomics Its objective is to enhance local capacity to undertake the economic analysis ofenvironmental problems and policies It uses a networking approach involving courses meetingstechnical support access to literature and opportunities for comparative research Member countries are Thailand Malaysia Indonesia the Philippines Vietnam Cambodia Lao PDR China and Papua New

Guinea

EEPSEA is supported by the International Development Research Centre (IDRC) the SwedishInternational Development Cooperation Agency (Sida) and the Canadian International Development Agency (CIDA)

EEPSEA publications are also available online at httpwwweepseaorg

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CKNOWLEDGEMENTS

We are sincerely grateful to the participants of the Climate Change Vulnerability Experts Consultation

Meeting in Bangkok in May 2008 Prof Rex Cruz Dr Khairulmaini Osman Salleh Dr Rizaldi Boer Ms

Rosa T Perez Mr Luong Quang Huy Mr Syamphone Sengchandala Mr Hoang Minh Hien Mr

Nathaniel C Bantayan Mr Heng Chan Thoeun Dr Suppakorn Chinvanno Dr Anond Snidvongs Dr

Bui Dung The and Dr Orapan Nabangchang for their invaluable inputs on this assessment We are also

deeply appreciative of Dr Richard Fuchs for his insightful suggestions on the conceptualization of this

study and for funding this project through IDRCs Regional Activity Funds We further thank Ms Ang

Cheng Hiang for the assisting in the production and Mr Megananda of the Center for Economics and

Development Studies (CEDS) Padjadjaran University for his excellent research assistance The authors

are fully responsible for any errors in this assessment

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TABLE OF CONTENTS

10 INTRODUCTION 1

20 OBJECTIVES 1

30 METHODOLOGY AND DATA 2

31 Vulnerability Assessment 3

32 Generating the Component Maps for the Vulnerability Assessment 4

321 Climate-related hazard maps 5

322 Human and ecological sensitivity maps 7

323 Adaptive capacity map 8

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP OFSOUTHEAST ASIA 10

50 CONCLUDING REMARKS 14

REFERENCES 14

APPENDICES 15

Appendix 1 Sources of Data 15

Appendix 2 Climate Hazard Maps of Southeast Asia 18

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003) 18

Appendix 2B Flood frequency (event per year from 1980-2001) 18

Appendix 2C Drought frequency (event per year from 1980-2000) 19

Appendix 2D Landslide exposure (2005) 19

Appendix 2E Sea level rise (5-m inundation zone) 20

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia 21

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard) 21

Appendix 3B List of vulnerable provincesdistricts (country standard) 24

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ABSTRACT

This paper provides information on the sub-national areas (regionsdistrictsprovinces) most vulnerable

to climate change impacts in Southeast Asia This assessment was carried out by overlaying climate hazard

maps sensitivity maps and adaptive capacity maps following the vulnerability assessment framework of

the United Nationsrsquo Inter-governmental Panel on Climate Change (IPCC) The study used data on the

spatial distribution of various climate-related hazards in 530 sub-national areas of Indonesia Thailand

Vietnam Lao PDR Cambodia Malaysia and the Philippines Based on this mapping assessment all the

regions of the Philippines the Mekong River Delta in Vietnam almost all the regions of Cambodia

North and East Lao PDR the Bangkok region of Thailand and West Sumatra South Sumatra West Java

and East Java of Indonesia are among the most vulnerable regions in Southeast Asia

Keywords climate change vulnerability Southeast Asia

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1

10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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4

Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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6

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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7

322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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16

Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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20

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Comments should be sent to

Dr Arief Anshory Yusuf (email ariefyusuffeunpadacid) orDr Herminia Francisco (email hfranciscoidrcorgsg)

Economy and Environment Program for Southeast Asia (EEPSEA)22 Cross Street 02-55 South Bridge Court Singapore 048421 Tel 65 6438 7877 Fax 65 6438 4844httpwwweepseaorg

EEPSEA was established in May 1993 to support research and training in environmental and resourceeconomics Its objective is to enhance local capacity to undertake the economic analysis ofenvironmental problems and policies It uses a networking approach involving courses meetingstechnical support access to literature and opportunities for comparative research Member countries are Thailand Malaysia Indonesia the Philippines Vietnam Cambodia Lao PDR China and Papua New

Guinea

EEPSEA is supported by the International Development Research Centre (IDRC) the SwedishInternational Development Cooperation Agency (Sida) and the Canadian International Development Agency (CIDA)

EEPSEA publications are also available online at httpwwweepseaorg

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CKNOWLEDGEMENTS

We are sincerely grateful to the participants of the Climate Change Vulnerability Experts Consultation

Meeting in Bangkok in May 2008 Prof Rex Cruz Dr Khairulmaini Osman Salleh Dr Rizaldi Boer Ms

Rosa T Perez Mr Luong Quang Huy Mr Syamphone Sengchandala Mr Hoang Minh Hien Mr

Nathaniel C Bantayan Mr Heng Chan Thoeun Dr Suppakorn Chinvanno Dr Anond Snidvongs Dr

Bui Dung The and Dr Orapan Nabangchang for their invaluable inputs on this assessment We are also

deeply appreciative of Dr Richard Fuchs for his insightful suggestions on the conceptualization of this

study and for funding this project through IDRCs Regional Activity Funds We further thank Ms Ang

Cheng Hiang for the assisting in the production and Mr Megananda of the Center for Economics and

Development Studies (CEDS) Padjadjaran University for his excellent research assistance The authors

are fully responsible for any errors in this assessment

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TABLE OF CONTENTS

10 INTRODUCTION 1

20 OBJECTIVES 1

30 METHODOLOGY AND DATA 2

31 Vulnerability Assessment 3

32 Generating the Component Maps for the Vulnerability Assessment 4

321 Climate-related hazard maps 5

322 Human and ecological sensitivity maps 7

323 Adaptive capacity map 8

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP OFSOUTHEAST ASIA 10

50 CONCLUDING REMARKS 14

REFERENCES 14

APPENDICES 15

Appendix 1 Sources of Data 15

Appendix 2 Climate Hazard Maps of Southeast Asia 18

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003) 18

Appendix 2B Flood frequency (event per year from 1980-2001) 18

Appendix 2C Drought frequency (event per year from 1980-2000) 19

Appendix 2D Landslide exposure (2005) 19

Appendix 2E Sea level rise (5-m inundation zone) 20

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia 21

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard) 21

Appendix 3B List of vulnerable provincesdistricts (country standard) 24

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ABSTRACT

This paper provides information on the sub-national areas (regionsdistrictsprovinces) most vulnerable

to climate change impacts in Southeast Asia This assessment was carried out by overlaying climate hazard

maps sensitivity maps and adaptive capacity maps following the vulnerability assessment framework of

the United Nationsrsquo Inter-governmental Panel on Climate Change (IPCC) The study used data on the

spatial distribution of various climate-related hazards in 530 sub-national areas of Indonesia Thailand

Vietnam Lao PDR Cambodia Malaysia and the Philippines Based on this mapping assessment all the

regions of the Philippines the Mekong River Delta in Vietnam almost all the regions of Cambodia

North and East Lao PDR the Bangkok region of Thailand and West Sumatra South Sumatra West Java

and East Java of Indonesia are among the most vulnerable regions in Southeast Asia

Keywords climate change vulnerability Southeast Asia

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1

10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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2

30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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23

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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CKNOWLEDGEMENTS

We are sincerely grateful to the participants of the Climate Change Vulnerability Experts Consultation

Meeting in Bangkok in May 2008 Prof Rex Cruz Dr Khairulmaini Osman Salleh Dr Rizaldi Boer Ms

Rosa T Perez Mr Luong Quang Huy Mr Syamphone Sengchandala Mr Hoang Minh Hien Mr

Nathaniel C Bantayan Mr Heng Chan Thoeun Dr Suppakorn Chinvanno Dr Anond Snidvongs Dr

Bui Dung The and Dr Orapan Nabangchang for their invaluable inputs on this assessment We are also

deeply appreciative of Dr Richard Fuchs for his insightful suggestions on the conceptualization of this

study and for funding this project through IDRCs Regional Activity Funds We further thank Ms Ang

Cheng Hiang for the assisting in the production and Mr Megananda of the Center for Economics and

Development Studies (CEDS) Padjadjaran University for his excellent research assistance The authors

are fully responsible for any errors in this assessment

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TABLE OF CONTENTS

10 INTRODUCTION 1

20 OBJECTIVES 1

30 METHODOLOGY AND DATA 2

31 Vulnerability Assessment 3

32 Generating the Component Maps for the Vulnerability Assessment 4

321 Climate-related hazard maps 5

322 Human and ecological sensitivity maps 7

323 Adaptive capacity map 8

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP OFSOUTHEAST ASIA 10

50 CONCLUDING REMARKS 14

REFERENCES 14

APPENDICES 15

Appendix 1 Sources of Data 15

Appendix 2 Climate Hazard Maps of Southeast Asia 18

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003) 18

Appendix 2B Flood frequency (event per year from 1980-2001) 18

Appendix 2C Drought frequency (event per year from 1980-2000) 19

Appendix 2D Landslide exposure (2005) 19

Appendix 2E Sea level rise (5-m inundation zone) 20

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia 21

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard) 21

Appendix 3B List of vulnerable provincesdistricts (country standard) 24

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ABSTRACT

This paper provides information on the sub-national areas (regionsdistrictsprovinces) most vulnerable

to climate change impacts in Southeast Asia This assessment was carried out by overlaying climate hazard

maps sensitivity maps and adaptive capacity maps following the vulnerability assessment framework of

the United Nationsrsquo Inter-governmental Panel on Climate Change (IPCC) The study used data on the

spatial distribution of various climate-related hazards in 530 sub-national areas of Indonesia Thailand

Vietnam Lao PDR Cambodia Malaysia and the Philippines Based on this mapping assessment all the

regions of the Philippines the Mekong River Delta in Vietnam almost all the regions of Cambodia

North and East Lao PDR the Bangkok region of Thailand and West Sumatra South Sumatra West Java

and East Java of Indonesia are among the most vulnerable regions in Southeast Asia

Keywords climate change vulnerability Southeast Asia

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10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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6

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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7

322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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TABLE OF CONTENTS

10 INTRODUCTION 1

20 OBJECTIVES 1

30 METHODOLOGY AND DATA 2

31 Vulnerability Assessment 3

32 Generating the Component Maps for the Vulnerability Assessment 4

321 Climate-related hazard maps 5

322 Human and ecological sensitivity maps 7

323 Adaptive capacity map 8

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP OFSOUTHEAST ASIA 10

50 CONCLUDING REMARKS 14

REFERENCES 14

APPENDICES 15

Appendix 1 Sources of Data 15

Appendix 2 Climate Hazard Maps of Southeast Asia 18

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003) 18

Appendix 2B Flood frequency (event per year from 1980-2001) 18

Appendix 2C Drought frequency (event per year from 1980-2000) 19

Appendix 2D Landslide exposure (2005) 19

Appendix 2E Sea level rise (5-m inundation zone) 20

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia 21

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard) 21

Appendix 3B List of vulnerable provincesdistricts (country standard) 24

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ABSTRACT

This paper provides information on the sub-national areas (regionsdistrictsprovinces) most vulnerable

to climate change impacts in Southeast Asia This assessment was carried out by overlaying climate hazard

maps sensitivity maps and adaptive capacity maps following the vulnerability assessment framework of

the United Nationsrsquo Inter-governmental Panel on Climate Change (IPCC) The study used data on the

spatial distribution of various climate-related hazards in 530 sub-national areas of Indonesia Thailand

Vietnam Lao PDR Cambodia Malaysia and the Philippines Based on this mapping assessment all the

regions of the Philippines the Mekong River Delta in Vietnam almost all the regions of Cambodia

North and East Lao PDR the Bangkok region of Thailand and West Sumatra South Sumatra West Java

and East Java of Indonesia are among the most vulnerable regions in Southeast Asia

Keywords climate change vulnerability Southeast Asia

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10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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2

30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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4

Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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6

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

Page 6: Climate Change Vulnerability Mapping for Southeast Asia

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ABSTRACT

This paper provides information on the sub-national areas (regionsdistrictsprovinces) most vulnerable

to climate change impacts in Southeast Asia This assessment was carried out by overlaying climate hazard

maps sensitivity maps and adaptive capacity maps following the vulnerability assessment framework of

the United Nationsrsquo Inter-governmental Panel on Climate Change (IPCC) The study used data on the

spatial distribution of various climate-related hazards in 530 sub-national areas of Indonesia Thailand

Vietnam Lao PDR Cambodia Malaysia and the Philippines Based on this mapping assessment all the

regions of the Philippines the Mekong River Delta in Vietnam almost all the regions of Cambodia

North and East Lao PDR the Bangkok region of Thailand and West Sumatra South Sumatra West Java

and East Java of Indonesia are among the most vulnerable regions in Southeast Asia

Keywords climate change vulnerability Southeast Asia

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1

10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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2

30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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4

Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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6

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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7

322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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8

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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16

Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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18

Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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19

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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22

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

Page 7: Climate Change Vulnerability Mapping for Southeast Asia

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10 INTRODUCTION

The United Nations Climate Change Conference held in Bali Indonesia in December 2007

acknowledged among other things the need for enhanced action on adaptation and the provision of

financial resources for it This in turn implies the need for financial and technology transfer from the

rich to the poor countries In general most developing countries in Asia have the least capacity to adapt

to climate change and are therefore in need of whatever external support they can get to build their

capacity (Francisco 2008)

As the long history of international climate change agreements tells us resource transfers from rich to

poor countries not only require a common and shared vision among the countries but also involve long

and complex political processes Acknowledging the fact that in a resource-constrained world there is a

benefit and cost to every action it is then essential for the resources available to be well targeted to the

people who need them the most those located in the areas most vulnerable to climate change

The identification and characterization of the vulnerable communities and sectors were identified as

priority concerns by the participants of the EEPSEA Climate Change Adaptation Conference held in Bali

in February 2008 Identification of the most vulnerable groups by way of determining the most vulnerable

regions within countries and in Southeast Asia as a whole is thus an urgent task for development agencies

This paper addresses this need

20 OBJECTIVES

The general objective of this study is to identify which regions in Southeast Asia are the most vulnerable

to climate change It is expected that this information will be useful to policy-makers of the region as well

as external donors in better targeting their support towards climate change efforts The specific objectives

are as follows

1 To identify which sub-national areasunits (regions provinces or districts depending on the

availability of the data) of Southeast Asian countries (Thailand Vietnam Laos Cambodia Indonesia

Malaysia and Philippines) are the most vulnerable to climate change

2 To show these vulnerable areas in a map for ease of reference of interested parties

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30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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23

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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30 METHODOLOGY AND DATA

Identifying climate change vulnerability requires a clear conceptual framework We started by adopting

the concept contained in the Third Assessment Report of the IPCC where vulnerability is defined as

ldquoThe degree to which a system is susceptible to or unable to cope with the adverse effects of climate

change including climate variability and extremes Vulnerability is a function of the character magnitude

and rate of climate variation to which a system is exposed its sensitivity and its adaptive capacityrdquo (IPCC

2001 p995) Vulnerability can thus be defined as a function of exposure sensitivity and adaptive

capacity or

Vulnerability = f(exposure sensitivity adaptive capacity)

In the IPCC report exposure is defined as ldquothe nature and degree to which a system is exposed to

significant climatic variationsrdquo sensitivity is defined as ldquothe degree to which a system is affected either

adversely or beneficially by climate-related stimuli1rdquo and adaptive capacity is defined as ldquothe ability of a

system to adjust to climate change (including climate variability and extremes) to moderate the potential

damage from it to take advantage of its opportunities or to cope with its consequencesrdquo

We used the above conceptual framework to do a lsquoquickrsquo assessment of the lsquocurrentrsquo vulnerability of

selected Southeast Asian countries based on past as well as the most recently available data We

emphasize the term lsquoquickrsquo as this effort should be considered as a first cut of sorts since this work was

largely dependent on whatever information we could get from public sources (such as the internet) and

climate change experts in the region We used the inputs of a select group of climate and social scientists

from the region obtained through a Climate Change Experts Consultation Meeting held with them in

Bangkok in the middle of 2008

The main limitation of our assessment was our inability to factor in projections of climate change and

socio-economic conditions for the coming years However given that the future trajectory of climate

change events and socio-economic conditions is so uncertain we feel that such an analysis would be hard

to sell in any case It is far more reliable to use historical data as current vulnerability is likely to worsen

than improve Naturally there is room for fine-tuning this assessment to take into account scientifically

acceptable projections on future climate change impacts as well as projected changes in socio-economic

conditions Detailed sub-national information on the various indicators of adaptive capacity should be

collected given more time and resources However we shall leave such improvements to future studies

on this topic

Our motivation in coming up with this map is to provide some indications on how the limited

(developmental and research) resources available for adaptation work could be best directed across

1 The effect may be direct (eg a change in crop yield in response to a change in the mean range or variability of temperature) orindirect (eg damages caused by an increase in the frequency of coastal flooding due to sea level rise)

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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3

countries in the region and across sub-national areas within a country The identification of specific

adaptation support or research for the different locales should then be carried out

31 Vulnerability Assessment

To identify the vulnerable regions we constructed an index of the climate change vulnerability of sub-

national administrative areas in seven countries in Southeast Asia ie Vietnam Laos Cambodia

Thailand Malaysia the Philippines and Indonesia The assessment considers 530 sub-national areas

comprising 341 districts ( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces

( khoueng ) in Lao PDR 14 states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat )

in Thailand and 53 provinces ( tinhthanh pho ) in Vietnam

The climate change vulnerability index was derived through the following steps

bull We assessed exposure using information from historical records of climate-related hazards as we

considered past exposure to climate risks as the best available proxy for future climate risks

bull We obtained climate hazard maps for five climate-related risks tropical cyclones floods landslides

droughts and sea level rise

bull We used population density as a proxy for human sensitivity to climate-hazard exposure The

assumption here is that regions that are relatively less inhabited will be less vulnerable compared to

regions with high population densities given the same degree of exposure to climate hazards

bull In addition to the human aspect of vulnerability we also included ecological sensitivity of the region

using biodiversity information as a proxy variable A biodiversity-rich region measured by the

percentage of protected areas is thus considered here as more vulnerable than other areas to climate

hazards other things being equal

bull We constructed an index of adaptive capacity as a function of socio-economic factors technology

and infrastructure

Based on the above we constructed an index of the overall climate change vulnerability of the region

Figure 1 illustrates the steps we took in constructing the index

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4

Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Cyclone Risk Map [15]

Drought Risk Map [15]

Flood Risk Map [15]

Landslide Risk Map [15]

Sea Level Rise Map [15]

Multiple Hazard Map [13]

Adaptive Capacity [13]

Overall VulnerabilityPopulation Density ampProtected areas [13]

Figure 1 Method used in deriving the climate change vulnerability index

Note The figures in parenthesis indicate the weights given to the respective factors

32 Generating the Component Maps for the Vulnerability Assessment

As shown in Figure 1 we derived the overall climate change vulnerability index by overlaying a series of

maps These maps are described below (Please refer to Appendix 1 for the sources of the data used in

this vulnerability mapping project)

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321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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5

321 Climate hazard maps

First we obtained maps (in gridraster format) for five different climate hazards the frequency of

droughts floods and cyclones for about 20 years (1980-200013) physical exposure to landslides and

inundation zones of a five-meter sea level rise The maps of these five hazards are given in Appendix 2

Then to make the maps comparable we normalized each of them using the following formula

Zij =X ij ndash X iMIN

X iMAX ndash X iMIN

where Zij is the standardized climate hazard of type i of region j X ij is the unstandardized climate hazard

of type i of region j X iMAX is the maximum value of the climate hazard indicator over region j and X iMIN

is the minimum value of the climate hazard indicator over region j A similar standardization method is

used by the UNDP to calculate the Human Development Index

Thirdly we used the simple average of the five standardized climate hazard indicators thus overlaying all

five hazard maps onto one single multiple hazard map Since we did not have knowledge of the degree of

importance of each hazard in assessing the vulnerability we assumed equal weights for all

Figure 2 is the overall climate hazard map showing the combination of climate-related hazards (tropical

cyclones floods landslides droughts and sea level rise) and the hotspots in Southeast Asia The latter

includes the north-western and Mekong region of Vietnam the coastal regions of Vietnam facing the

South China Sea Bangkok and its surrounding areas in Thailand practically all the regions of the

Philippines and the western and eastern parts of Java Island Indonesia Table 1 lists the climate hazard

hotspots and their dominant hazards

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6

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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12

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Multiple Climate Hazard Index

000 - 004

004 - 009

009 - 014

014 - 018

018 - 024

024 - 031

031 - 039

039 - 047

047 - 060

060 - 100

Country Boundary

Figure 2 Multiple climate hazard map of Southeast Asia

Note For the legend the scale used is 0-1 indicating the lowest vulnerability level (0) to the highest vulnerability

level (1)

Table 1 Climate hazard hotspots and dominant hazards

Climate hazard hotspots Dominant hazards

Northwestern Vietnam Droughts

Eastern coastal areas of Vietnam Cyclones droughts

Mekong region of Vietnam Sea level rise

Bangkok and its surrounding area in Thailand Sea level rise floods

Southern regions of Thailand Droughts floods

The Philippines Cyclones landslides floods droughts

Sabah state in Malaysia Droughts

Western and eastern area of Java Island Indonesia Droughts floods landslides sea level rise

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322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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7

322 Human and ecological sensitivity maps

We obtained the population density maps from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) which showed the number of

people per square kilometer in 30-arc-second (1-km) resolution We converted the unit of observation

from the 1-km resolution into provincedistrict by averaging across administrative boundaries This

produced maps of average population density for each of the provincesdistricts in the region These

were used as indicators of human sensitivity

The ecological sensitivity map was obtained using data on protected areas from the Terrestrial Ecoregions

GIS Database of the World Wildlife Fund (WWF) We calculated the share of area within each

provincedistrict designated as protected areas over the total land area of the provincedistrict

The overall sensitivity map encompassing both human and ecological factors was derived using the

weighted averages of the standardized values of population density and protected area (as a share of total

area) for each of the provincesdistricts We chose to use a higher weight of 070 for population density

(with 030 for protected areas) because of the higher importance we attached to human sensitivity

Figure 3 shows the map of population density and protected areas The figure shows that Java is the most

densely populated island in the region Other highly populated areas are northeastern Vietnam (around

the capital) Bangkok and around the national capital of the Philippines

Thailand Cambodia and Lao PDR have relatively more protected areas compared to other countries in

the region The largest protected areas in Southeast Asia are the Foga region in Papua island Mount

Leuser National Park in northern Sumatra the Sungai Kayan-Sungai Mentarai Nature Reserve in North

Kalimantan the Thung Yai Naresuan Wildlife Sanctuary in eastern Thailand Palawan Island of the

Philippines the Nakai-Nam Theun National Biodiversity Conservation Park of Lao PDR and the

Mondulkiri Protected Forest of Cambodia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

Page 14: Climate Change Vulnerability Mapping for Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Protected areas

Population Density

High 444797

Low 0

Country Boundary

Figure 3 Human (population density) and ecological (protected areas) sensitivity map of Southeast Asia(2000)

323 Adaptive capacity map

Adaptive capacity is defined as the degree to which adjustments in practices processes or structures can

moderate or offset potential damage or take advantage of opportunities (from climate change) It can be

written in equation form as follows

Adaptive Capacity = f(socio-economic factors technology infrastructure)2

The Climate Change Experts Consultation Meeting held in Bangkok in mid-2008 resulted in an

operational framework to measure adaptive capacity using selected indicators We used lsquoexpert opinion

pollingrsquo to arrive at the weights assigned to the various climate change indicators shown in Figure 4

2 Initially included in the function of adaptive capacity was ldquopolicy and institutionsrsquo However due to lack of data availabilityacross sub-national areas in SEA the variable was dropped from this analysis

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9

SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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12

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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SOCIO-ECONOMICS

TECHNOLOGY

INFRASTRUCTURE

Human Development Index

Standard of Living

Longevity

Education

050

13

13

13

Poverty Incidence 028

Income Inequality 022

Electricity Coverage 053

Extent of Irrigation 047

Road Density 050

Communication 050

ADAPTIVE CAPACITY

050

025

025

Figure 4 Adaptive capacity assessment

Figure 5 below is a map showing the adaptive capacity of Southeast Asia3 Overall areas with relatively

high adaptive capacity lie in Thailand Malaysia and Vietnam whereas areas with relatively low adaptivecapacity are mostly found in Cambodia and Lao PDR

3 See Appendix 1 for details on the adaptive capacity calculations

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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17

Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

Page 16: Climate Change Vulnerability Mapping for Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend

Adaptive Capacity Index

000- 022

022 - 037

037 - 047

047 - 053

053 - 058

058 - 064

064 - 069

069 - 075

075 - 084

084 - 100

Country Boundary

Figure 5 Adaptive capacity map of Southeast Asia (2005)

40 OVERALL CLIMATE CHANGE VULNERABILITY MAP

OF SOUTHEAST ASIA

To obtain the overall index of climate change vulnerability we averaged each of the normalized indicators

of exposure (multiple hazard risk exposure) sensitivity (human and ecological) and adaptive capacity To

identify the vulnerable areas we ranked the regions according to the index and divided the list into four

equal parts Those provincesdistricts falling in the fourth quartile were considered the vulnerable areas

and further classified as mildly vulnerable moderately vulnerable or highly vulnerable

We used two different ways of ranking the areas first across the whole of Southeast Asia and second

within each of the selected countries4 This was done simply to rank priority areas for adaptation

interventions by different users of this mapping information Figure 6 shows the map of climate change

vulnerability in Southeast Asia while Figures 7 and 8 show the vulnerable areas by region (SEA) and

4 For the Southeast Asia standard the fourth quartile regions are further classified into three categories mild vulnerability (with an index interval of 033-046) moderate vulnerability (047-067) and high vulnerability (068-

100) For the country standard the index intervals for the mild moderate and high vulnerability categories are 018-042 043-065 and 066-100 respectively These categories were set using ArchMap software which best groupssimilar values and identifies big jumps in datasets

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country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

Page 17: Climate Change Vulnerability Mapping for Southeast Asia

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11

country standards respectively The two tables in Appendix 3 list the vulnerable areas showing the

vulnerability indices and components

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Climate Change Vulnerability

000 - 006

006 - 011

011 - 015

015 - 020

020 - 025

025 - 031

031 - 039

039 - 049

049 - 066

066 - 100

Figure 6 Climate change vulnerability map of Southeast Asia

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12

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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19

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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12

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (SEA std)

mildly vulnerable (033 - 046)

moderately vulnerable (047 - 067)

highly vulnerable (068 - 100)

Figure 7 Map of the most vulnerable areas in Southeast Asia (regional standard)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 550 1100275 Kilometers

Legend

Vulnerable regions (Country std)

mildly vulnerable (018 - 042)

moderately vulnerable (043 - 065)

highly vulnerable (066 - 100)

Figure 8 Map of the most vulnerable areas in Southeast Asia (country standard)

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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13

As can be seen from Figure 7 we identified the most vulnerable areas using the Southeast Asian standard

of those falling within the topfourth quartile These areas include all the regions of the Philippines the

Mekong River Delta region of Vietnam almost all the regions of Cambodia North and East Lao PDR

the Bangkok region of Thailand and the west and south of Sumatra and western and eastern Java in

Indonesia The Philippines unlike other countries in Southeast Asia is not only exposed to tropical

cyclones especially in the northern and eastern parts of the country but also to many other climate-

related hazards especially floods (such as in central Luzon and Southern Mindanao) landslides (due to the

terrain of the country) and droughts

Figure 8 reflects the most vulnerable regions within countries ie those in the top quartile relative to

other areas within each country Using this standard we find that in Malaysia the most vulnerable regions

are the states of Kelantan and Sabah In the Philippines the areas with the highest vulnerability are the

National Capital Region Southern Tagalog Cagayan Valley Central Luzon the Cordillera AdministrativeRegion and Bicol Province The National Capital Region of the Philippines which is densely populated

is particularly susceptible to multiple climate hazards (especially cyclones and floods)

In general these results provide no surprises as they confirm commonly-held suspicions that the most

vulnerable regions in Southeast Asia include the Mekong River Delta in Vietnam and Bangkok due to

their exposure to sea level rise as well as the northern part of the Philippines due to its exposure to

tropical cyclones

Notwithstanding this some surprises did arise Although most regions in Cambodia were relatively nothighly exposed to climate hazards except those sharing borders with the Mekong River Delta in northern

Vietnam (which is susceptible to flooding and sea level rise) almost all the provinces in Cambodia are

vulnerable due to their low adaptive capacity

In the overall assessment however the districts of Jakarta in Indonesia come out as the top most

vulnerable regions in Southeast Asia (see Appendix 3) Moreover the areas in western and eastern Java

are also vulnerable using the regional standard Central Jakarta ranks first in the overall vulnerability

assessment even though it has the highest adaptive capacity index This is because this district is the

intersection of all the climate-related hazards except tropical cyclones It is frequently exposed to regular

flooding but most importantly it is highly sensitive because it is among the most densely-populated

regions in Southeast Asia Areas in western Java are also highly vulnerable due to exposure to multiple

hazards (namely floods and landslides) as well as having high population densities

Adaptive capacity seems to play important role in changing the spatial pattern of vulnerability Low

adaptive capacity has made Cambodia among the most vulnerable regions despite its relatively low

exposure to climate hazards On the other hand the high adaptive capacity of the eastern coast of

Vietnam which is susceptible to cyclones has managed to moderate its vulnerability hence it is notincluded among the most vulnerable areas of Southeast Asia This is not generally true however for

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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14

other areas where high adaptive capacity does not help to moderate exposure to climate risks Bangkok

and Jakarta are good examples Their high adaptive capacities are not enough to moderate their extreme

vulnerability brought about by their high population densities and significant exposure to climate hazards

(in particular sea level rise and floods)

50 CONCLUDING REMARKS

The identification of the areas most vulnerable to climate change risks in Southeast Asia is among the

most urgent of policy needs This assessment responds to this need by identifying which

provincesdistricts in Southeast Asian countries (namely Thailand Vietnam Laos Cambodia Indonesia

Malaysia and the Philippines) are the most vulnerable to climate change and producing a map to show

climate change vulnerability in the region We gathered data at province and district levels from various

sources and integrated them in a consistent and meaningful manner to produce a map indicating the areasmost vulnerable to climate change Despite data limitations it is expected that the output of this analysis

will be useful to policy-makers and donors in better targeting financial resources towards adaptation

measures undertaken in Southeast Asia

REFERENCES

Francisco H A 2008 Adaptation to Climate Change Needs and Opportunities in Southeast Asia Asean

Economic Bulletin 25 (1)

IPCC (Inter-governmental Panel on Climate Change) 2001 J McCarthy O Canziani N Leary D

Dokken and K White (eds) In Climate Change 2001 Impacts Adaptation and Vulnerability

Cambridge University Press Cambridge

Peduzzi P H Dao and C Herold 2005 Mapping Disastrous Natural Hazards Using Global Datasets

Natural Hazards 35 (2) 265 - 289

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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23

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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15

APPENDICES

Appendix 1 Sources of Data

The data used in this vulnerability assessment came from different sources and in various formats such as

the GIS map format (both gridraster and SHP) and EXCEL data format A detailed explanation of the

sources of the data and how the figures were calculated is given below

Sub-national Administrative Areas

Data on sub-national administrative areas was available in ESRI SHP format For sub-national

administrative areas (such as provinces) the data came from the GEODATA portal (the Environmental

Database httpgeodatagridunepchextrasdatasetlistphp) Since Indonesia was the biggest country in

terms of area instead of using provinces as the unit of analysis we used districts instead The data ondistrict administrative boundaries for Indonesia was obtained from BAKOSURTANAL (or the National

Coordinating Body for Land Surveys)

In all there were 530 sub-national areasunits in this assessment which were made up of 341 districts

( kabupatenkota ) in Indonesia 19 provinces ( khet ) in Cambodia 17 provinces ( khoueng ) in Lao PDR 14

states ( negeri ) in Malaysia 14 provinces in the Philippines 72 provinces ( changwat ) in Thailand and 53

provinces ( tinhthanh pho ) in Vietnam

Climate HazardsFrequency of tropical cyclones floods and droughts and exposure to landslides

The frequency of tropical cyclones floods and droughts was measured in terms of number of events per

year The cells in the maps indicate the number of events divided by the number of available years

(between 1980-2000 for droughts 1980-2001 for floods and 1980 and 2003 for cyclones) Details on the

construction of this map can be obtained from Peduzzi Dao and Herold (2005) The data in grid map

format is available from the PREVIEW website at

httpwwwgridunepchactivitiesearlywarningpreviewdatapreviewindex_aboutphp

The map of exposure to landslides is based upon the dataset from the Norwegian Geotechnical Institute

(NGI) The hazards mapping of NGI incorporates a range of data including slope soil soil moisture

conditions precipitation seismicity and temperature Shuttle Radar Topography Mission (SRTM)

elevation data at 30-arc-second resolution is incorporated Hazard values 4 and below are considered

negligible and only values from 5ndash9 are utilized for analysis To ensure compatibility with other datasets 1

is added to each of the values to produce a hazard ranking ranging from 6ndash10 This dataset is the result of

the collaboration among the Center for Hazards and Risk Research (CHRR) the Norwegian

Geotechnical Institute (NGI) and the Columbia University Center for International Earth Science andInformation Network (CIESIN)

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16

Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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23

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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25

PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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16

Sea level rise

The inundation zone map of a five-meter sea level rise was obtained from the Centers for the Remote

Sensing of Ice Sheets (CReSIS) at the University of Kansas USA and Haskell Indian Nations University

India Sea level rise or inundation zones were determined from the Global Land One-km Base Elevation(GLOBE) digital elevation model (DEM) (httpswwwcresiskueduresearchdatasea_level_rise)

Population Density

The population density map was obtained from the Urban Extent Database (GRUMP version 1) of the

Center for International Earth Science Information Network (CIESIN) Columbia University

(httpsedacciesincolumbiaedugpw) the International Food Policy Research Institute (IFPRI) the

World Bank and Centro Internacional de Agricultura Tropical (CIAT) The data is in geographic

coordinates of decimal degrees based on the World Geodetic System spheroid of 1984 (WGS84) in 30-

arc-second (1-km) resolution

Biodiversity Areas Declared as NationalProtected Parks

Data on nationalprotected parks as well as maps were obtained from the Terrestrial Ecoregions GIS

Database of the World Wildlife Fund (WWF) at

httpwwwworldwildlifeorgsciencedataitem1875html

Adaptive Capacity

Human Development Index

The Human Development Index (HDI) was calculated using the following formula

HDI = (13)[ Standard of Living Index]

+ (13)[ Life Expectancy at Birth Index]

+ (13)[ Education Index ]

The Standard of Living Index was calculated using the Gross Domestic Regional Product (GDRP) per

population (per capita) standardized using Purchasing Power Parity (PPP) for the year 2005 The GDRP

data was obtained from different sources while the PPP exchange rate was obtained from the World

Bankrsquos World Development Indicators (WDI)

The Life Expectancy at Birth data was obtained from various sources such as country reports on the

Human Development Index of the United Nations Development Program (UNDP)

Education was measured using literacy rates the data of which was obtained from various sources such as

the UNDPrsquos country reports on the HDI

The index of each of the three components of the HDI was calculated following the methods used by the

UNDP

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17

Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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19

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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20

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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21

Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Poverty incidences and inequality (Gini coefficient)

Poverty incidences and the Gini coefficients for each of the provincesdistricts of Vietnam Malaysia

Cambodia the Philippines and Thailand were obtained from various sources such as the UNDPrsquos

country reports on the HDI and the Asian Development Bank (ADB) For Indonesia and Lao PDR theirpoverty incidences and Gini coefficients were calculated directly using the Indonesian Socio-economic

Survey (SUSENAS) and the Lao Socio-economic Survey (LECS3) data respectively

Technology and infrastructure

We defined electricity coverage as the percentage of household with access to electricity and the extent of

irrigation as the percentage of irrigated agricultural land Road density was defined as the length of road

per square kilometer Communication was defined as the number of fixed phone lines per person The

data for all these came from various sources including the websites of the national statistics offices of thedifferent Southeast Asian countries

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Appendix 2 Climate Hazard Maps of Southeast Asia

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Cyclone Frequency

High 2501

Low 00056

Appendix 2A Tropical cyclone frequency (event per year from 1980-2003)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Flood Frequency

High 0762

Low 0000

Appendix 2B Flood frequency (event per year from 1980-2001)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Country Boundary

Annual Drought Frequency

High 0454545

Low 0000000

Appendix 2C Drought frequency (event per year from 1980-2000)

Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 530 1060265 Kilometers

Legend6

7

8

9

10

Country Boundary

Appendix 2D Landslide exposure (2005)

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Thailand

Indonesia

Laos

Vietnam

Cambodia

Malaysia

Philippines

reg0 560 1120280 Kilometers

Legend

Sea Level Rise (5m)

Country Boundary

Appendix 2E Sea level rise (5-m inundation zone)

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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Appendix 3 List of Vulnerable ProvincesDistricts in Southeast Asia

Appendix 3A List of vulnerable provincesdistricts (Southeast Asia standard)

CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

CAMBODIA

Mondol Kiri 083 4 002 037 099 3 056 42 1409 520 043

Rotanokiri 078 6 005 025 100 9 037 121 1409 520 042

Kampong Spoe 067 11 022 016 075 91 024 730 1029 520 051

Preah Vihear 064 13 001 026 082 11 038 152 1409 520 049

Pouthisat 056 24 017 027 050 31 041 428 1347 428 056

Takev 050 32 037 001 048 254 000 901 1208 321 054

Kandal 050 33 040 002 043 428 000 1243 1304 321 055

Kampot 049 35 022 018 044 122 026 603 1714 268 053

Kaoh Kong 049 37 018 029 036 10 044 192 1409 268 051

Kampong Chhnang 047 45 014 007 060 91 009 513 1258 428 052

Prey Veng 045 51 029 001 047 208 000 1044 1163 321 054

Batdambang 044 57 006 017 053 75 025 998 1105 428 053Stoeng Treng 043 62 002 006 066 8 009 104 1409 520 051

Siemreab-Otdar M 043 65 005 014 055 50 021 861 1230 428 053

Kampong Thum 042 69 004 008 060 49 012 682 1412 428 051

Svay Rieng 041 73 023 001 047 192 000 538 948 321 054

Kracheh 037 92 001 004 061 23 006 334 1409 520 053

INDONESIA

Central Jakarta 100 1 065 100 000 20419 000 889 21708 32 089

North Jakarta 100 2 100 061 004 12400 000 1446 9822 63 085

West Jakarta 090 3 077 068 004 9993 029 2093 7841 27 083

East Jakarta 079 5 065 064 003 13116 000 2391 5371 30 082

South Jakarta 077 8 065 060 004 12282 000 2001 8375 32 084

Kota Bandung 077 9 058 065 006 13298 000 2289 2374 37 075

Kota Surabaya 075 10 070 053 003 10729 000 2612 5761 75 079

Kota Bekasi 065 12 064 040 006 8260 000 1993 1496 36 072

Kota Bogor 063 14 065 033 008 6664 000 891 1017 89 070

Kota Depok 063 15 065 034 007 6959 000 1375 876 29 071

Kota Palembang 060 16 072 025 005 5012 000 1342 2112 94 074

Kota Tangerang 060 17 065 033 004 6638 000 1452 3679 47 076

Tangerang 060 18 078 013 010 2459 002 3259 1262 77 068

West Lampung 060 19 045 039 018 74 058 378 833 256 065

Jayawijaya 058 20 020 023 056 7 034 210 677 503 044

Kota Malang 058 21 049 045 005 9106 000 790 3211 69 075

Puncak Jaya 057 22 020 027 049 6 041 111 520 538 061

Jembrana 056 23 048 038 008 299 055 247 1414 93 069

Bogor 055 25 072 011 009 1366 007 3829 1562 124 070

Garut 053 26 073 007 011 678 006 2196 1015 176 067

Lebak 051 28 069 006 012 356 006 1155 724 122 063

Bandung 050 29 069 009 008 1438 003 4037 1302 136 071

Sumedang 050 31 069 008 009 692 007 1014 1189 136 069

Sukabumi 049 39 062 011 011 567 012 2169 936 168 067

Cianjur 048 41 064 007 011 568 006 2080 834 178 066

Buleleng 046 47 050 019 010 437 026 600 1106 93 067

Pandeglang 046 48 052 016 011 455 020 1063 805 146 064

Tanjung Jabung 045 49 047 018 013 43 027 204 1081 136 068

Karawang 045 50 063 005 011 983 000 1926 1661 148 067

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

South East Aceh 045 53 033 034 010 20 050 168 1002 253 070

Kota Balikpapan 045 54 040 031 006 468 044 470 3939 37 079

Bekasi 045 55 062 009 006 1891 000 1984 5058 69 077Paniai 044 56 026 014 036 10 021 114 596 518 054

South Bengkulu 043 58 037 021 017 56 030 130 855 380 067

Bangkalan 043 59 052 003 019 618 000 890 769 322 057

Purwakarta 043 61 060 005 009 731 003 753 1790 147 070

Sidoarjo 043 63 051 016 007 3321 000 1697 3100 141 076

Tanggamus 042 67 049 010 015 216 013 821 865 204 066

Majalengka 042 68 057 004 012 848 000 1168 725 195 064

Ponorogo 041 72 054 004 013 608 002 870 751 173 062

Kota Blitar 040 78 049 013 008 2587 000 127 1187 112 071

Tasik Malaya 039 79 054 003 011 682 000 1619 679 183 067

South Aceh 039 80 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 81 047 013 007 2724 000 171 1322 92 071

Serang 038 84 046 009 012 945 007 1755 1154 112 065

Dairi 038 88 048 007 011 99 010 265 1567 196 070

Gorontalo 037 91 030 015 020 100 022 422 465 328 063

Sampang 037 93 039 003 023 604 000 835 636 390 050

Magetan 037 94 051 004 010 833 000 617 1031 169 068

Indramayu 037 97 046 004 014 916 000 1689 873 185 060

Ciamis 037 98 049 005 010 573 003 1512 969 151 068

Madiun 037 100 049 004 012 737 000 642 851 214 063

Lahat 036 101 031 018 014 98 027 547 1174 297 069

East Lombok 036 102 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 104 047 001 015 56 001 660 964 245 067

Kota Bitung 036 106 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 107 048 002 013 45 003 631 1876 169 074

Malang 035 108 044 007 011 776 005 2336 1194 160 065

Subang 035 109 048 004 010 699 001 1380 981 169 066

Trenggalek 035 110 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 111 051 006 005 1248 000 589 1539 29 070

Merauke 035 112 037 009 016 2 013 156 1834 339 065

West Sumba 035 113 010 003 048 96 005 400 382 421 053

Nganjuk 035 115 046 003 012 703 000 990 949 238 065

Kediri 035 117 045 005 011 953 000 1429 860 179 066

Lamongan 035 118 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 120 043 017 001 3457 000 249 18983 135 086Manggarai 034 122 027 007 026 99 010 484 396 321 061

Boyolali 034 123 036 013 011 844 013 923 952 175 066

Ngawi 034 124 044 003 013 592 000 828 727 234 062

Agam 034 125 039 011 010 189 015 425 1391 132 071

Langkat 034 126 027 023 010 160 033 996 1326 208 071

Jombang 034 128 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 129 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 130 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 131 043 002 013 482 000 1229 921 264 063

Kota Padang 033 132 045 007 006 1511 000 800 2895 43 077

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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CONPROV UL RANK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

LAO PDR

Phongsali 049 38 028 009 047 12 013 166 973 443 048

Houaphan 048 42 022 017 043 18 025 281 1113 454 050Louang Namtha 045 52 038 006 033 14 010 145 1511 202 049

Oudomxai 042 66 030 000 044 19 000 265 962 425 050

Saravan 040 76 010 017 044 30 025 324 919 476 047

Khammouan 040 77 018 029 023 21 043 337 1496 324 056

Bokeo 035 114 032 001 029 18 002 145 1238 211 052

Attapeu 034 121 007 015 038 14 023 112 1333 406 057

PHILIPPINES

National Capital Region 078 7 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 27 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 30 067 011 009 541 012 9721 1934 134 073

Cagayan Valley 050 34 056 013 016 110 018 3051 1328 268 068

Bicol 049 36 059 004 021 255 004 5110 1151 436 069

Ilocos 049 40 069 003 011 335 002 4546 1342 165 071

Southern Tagalog 047 44 050 022 009 319 031 14300 4669 149 076

Eastern Visayas 043 60 048 001 025 163 001 3913 1159 454 065

Northern Mindanao 041 74 048 005 017 148 007 3952 2575 337 071

Central Visayas 038 86 045 005 017 388 004 6399 2347 373 072

Western Mindanao 038 87 043 002 021 207 001 3230 1764 398 065

Western Visayas 037 96 043 006 016 299 007 6844 2227 264 071

Southern Mindanao 036 103 047 004 013 174 004 4157 2412 225 072

Central Mindanao 036 105 041 004 018 186 004 3829 1993 280 067

THAILAND

Krung Thep 047 43 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 75 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 82 059 005 003 1061 000 896 5236 03 080

Trang 034 119 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 127 054 003 003 538 000 452 31051 08 090

VIETNAM

Lai Chau 047 46 042 015 023 33 022 506 1313 410 043

Dong Thap 043 64 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 70 064 003 005 586 000 1066 1903 165 074

Can Tho 041 71 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 83 055 002 010 443 000 958 1841 307 068

An Giang 038 85 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 89 059 004 004 748 000 1657 1839 174 073Soc Trang 038 90 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 95 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 99 057 006 002 1179 000 1813 1493 99 077

Minh Hai 035 116 052 005 005 267 005 1752 2034 214 072

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

Tasik Malaya 039 42 054 003 011 682 000 1619 679 183 067

South Aceh 039 43 029 028 011 30 041 189 1572 277 070

Kota Madiun 039 44 047 013 007 2724 000 171 1322 92 071Serang 038 45 046 009 012 945 007 1755 1154 112 065

Dairi 038 46 048 007 011 99 010 265 1567 196 070

Gorontalo 037 47 030 015 020 100 022 422 465 328 063

Sampang 037 48 039 003 023 604 000 835 636 390 050

Magetan 037 49 051 004 010 833 000 617 1031 169 068

Indramayu 037 50 046 004 014 916 000 1689 873 185 060

Ciamis 037 51 049 005 010 573 003 1512 969 151 068

Madiun 037 52 049 004 012 737 000 642 851 214 063

Lahat 036 53 031 018 014 98 027 547 1174 297 069

East Lombok 036 54 023 019 021 675 024 1039 563 284 054

Ogan Komering Hilir 036 55 047 001 015 56 001 660 964 245 067

Kota Bitung 036 56 033 024 006 283 033 164 2557 92 076

Indragiri Hilir 036 57 048 002 013 45 003 631 1876 169 074

Malang 035 58 044 007 011 776 005 2336 1194 160 065

Subang 035 59 048 004 010 699 001 1380 981 169 066

Trenggalek 035 60 047 003 012 539 000 665 662 229 066

Kota Banjarmasin 035 61 051 006 005 1248 000 589 1539 29 070

Merauke 035 62 037 009 016 2 013 156 1834 339 065

West Sumba 035 63 010 003 048 96 005 400 382 421 053

Nganjuk 035 64 046 003 012 703 000 990 949 238 065

Kediri 035 65 045 005 011 953 000 1429 860 179 066

Lamongan 035 66 046 003 012 706 000 1187 830 237 064

Kota Kediri 034 67 043 017 001 3457 000 249 18983 135 086

Manggarai 034 68 027 007 026 99 010 484 396 321 061

Boyolali 034 69 036 013 011 844 013 923 952 175 066

Ngawi 034 70 044 003 013 592 000 828 727 234 062

Agam 034 71 039 011 010 189 015 425 1391 132 071

Langkat 034 72 027 023 010 160 033 996 1326 208 071

Jombang 034 73 043 006 011 1142 000 1222 991 228 067

Ogan Komering Ulu 033 74 038 011 010 112 015 255 1673 177 072

Padang Pariaman 033 75 042 006 010 295 007 378 1325 142 069

Bojonegoro 033 76 043 002 013 482 000 1229 921 264 063

Kota Padang 033 77 045 007 006 1511 000 800 2895 43 077

Sumenep 033 78 039 002 017 483 000 1005 1027 330 059

Pamekasan 033 79 038 004 015 881 000 763 537 311 057 Tabanan 033 80 040 010 008 400 012 398 1210 93 071

Temanggung 032 81 042 004 011 900 000 688 737 147 068

Blitar 032 82 043 004 011 727 000 1066 1056 165 067

Kota Padang Panjang 032 83 047 004 006 921 000 45 1741 44 074

Bangli 032 84 047 002 009 423 000 209 1059 68 066

LAO PDR

Phongsali 049 1 028 009 047 12 013 166 973 443 048

Houaphan 048 2 022 017 043 18 025 281 1113 454 050

Louang Namtha 045 3 038 006 033 14 010 145 1511 202 049

Oudomxai 042 4 030 000 044 19 000 265 962 425 050

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black

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PROV UL RNK CHAZ SENS ADAP PDEN PROT POP INC POV HDI

MALAYSIA

Sabah 023 1 031 004 007 33 006 2932 6964 161 080

Kelantan 020 2 025 005 007 72 008 1506 4358 125 081Pulau Pinang 018 3 025 006 004 1212 000 1469 15682 19 088

PHILIPPINES

National Capital Region 078 1 054 071 005 14495 000 11600 6205 43 081

Cordillera Adm Region 051 2 070 005 013 78 007 1521 3111 145 071

Central Luzon 050 3 067 011 009 541 012 9721 1934 134 073

THAILAND

Krung Thep 047 1 061 020 000 4162 000 1232 18710 05 088

Samut Prakan 041 2 059 009 003 1853 000 1078 24321 98 089

Nonthaburi 039 3 059 005 003 1061 000 896 5236 03 080

Trang 034 4 041 014 006 123 020 602 4781 07 080

Samut Sakhon 034 5 054 003 003 538 000 452 31051 08 090

Chachoengsao 031 6 043 008 004 134 011 648 14963 49 086

Surat Thani 031 7 035 015 005 69 022 947 6377 08 082

Nakhon Si Thammarat 029 8 040 007 006 153 010 1504 4080 28 079

Satun 029 9 035 011 006 94 016 278 4584 65 080

Nakhon Nayok 028 10 026 020 005 118 029 251 4014 10 079

Ranong 026 11 033 010 006 47 014 178 4950 03 080

Uthai Thani 025 12 011 027 008 44 040 327 2899 87 076

Phatthalung 025 13 024 016 006 155 023 815 3205 33 078

Phetchaburi 025 14 014 026 004 70 039 501 5907 22 080

Pattani 024 15 036 002 007 309 000 21300 3642 163 076

Kanchanaburi 024 16 009 029 006 40 043 826 4074 88 079

Nakhon Pathom 024 17 039 002 003 381 000 809 8029 05 083

Tak 024 18 008 026 009 29 039 522 3506 209 075

VIETNAM

Lai Chau 047 1 042 015 023 33 022 506 1313 410 043

Dong Thap 043 2 065 003 006 498 001 1494 2975 193 072

Vinh Long 042 3 064 003 005 586 000 1066 1903 165 074

Can Tho 041 4 064 003 005 578 000 1814 2123 149 072

Tra Vinh 038 5 055 002 010 443 000 958 1841 307 068

An Giang 038 6 057 004 005 604 002 1976 2084 136 069

Tien Giang 038 7 059 004 004 748 000 1657 1839 174 073

Soc Trang 038 8 054 002 010 372 000 1194 1393 298 068

Ben Tre 037 9 055 003 007 650 000 1340 1663 317 072

Thai Binh 037 10 057 006 002 1179 000 1813 1493 99 077Minh Hai 035 11 052 005 005 267 005 1752 2034 214 072

Long An 033 12 053 002 004 334 000 1248 1695 109 073

Kien Giang 033 13 049 003 005 251 003 1351 3413 159 074

Notes

1 VUL Climate change vulnerability index RANK Rank of climate change vulnerability index (across SEA) CHAZ Multipleclimate hazard index SENS Sensitivity index ADAP Index of inverse adaptive capacity PDEN Population density in 2000(populationkm2 ) PROT Protected area ( of total area) POP population (thousand) INC per capita income in 2005(US$PPP) POV Poverty incidence HDI Human Development Index2 Color coding High vulnerability red bold moderate vulnerability black bold mild vulnerability black