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Environmental Vulnerability Mapping in LiberiaWork in Progress (July 2006)
For the latest version of this document visit http://postconflict.unep.ch/liberia/displacement
United Nations Environment ProgrammePost-Conflict Branch
15, Chemin des AnémonesCH-1219 Châtelaine, Geneva
SwitzerlandTel.: +41 (0)22 917 85 30Fax: +41 (0)22 917 80 64http://postconflict.unep.ch
Liberia Environmental Vulnerability Mapping
Table of Contents
1 Introduction.....................................................................................................................................1
1.1 Definitions............................................................................................................................... 2
2 Summary........................................................................................................................................ 3
3 Developing an Environmental Vulnerability Methodology.............................................................. 4
3.1 Context................................................................................................................................... 4
3.2 Understanding Environmental Vulnerability............................................................................4
3.3 Available Data Sources.......................................................................................................... 5
3.3.1 Terrain Morphology and Derived Hydrology................................................................... 6
3.3.2 Land Cover......................................................................................................................9
3.4 A Simple Model of Environmental Vulnerability....................................................................11
3.4.1 Likelihood of Impact – Proximity and Accessibility........................................................11
3.4.2 Extent – Degree of Loss of Value................................................................................. 14
3.5 Protected Areas.................................................................................................................... 20
3.6 Ecosystem Service Value Map ............................................................................................ 20
3.7 Combining Hazard Impact Potential and Value in a Vulnerability Model..............................22
3.7.1 Interpreting the Vulnerability Map................................................................................. 24
3.7.2 Vulnerability Map Examples..........................................................................................25
4 Running the Model.......................................................................................................................29
4.1 Step 1 – Data Preparation - Camp Locations.......................................................................29
4.2 Step 2 - Definition of Land Characteristics from Existing Sources....................................... 32
4.3 Step 3 – Calculating Proximity and Accessibility.................................................................. 32
4.4 Step 4 – Definition of Environmental Value – Dimension 2.................................................. 35
4.5 Step 5 Combining Hazard Impact Potential and Value in a Vulnerability Model.................. 36
5 Drainage and Catchment Analysis...............................................................................................38
5.1 Ecological Service Value by Catchment...............................................................................40
5.2 Drainage Concentration........................................................................................................41
6 Cartographic Vulnerability Maps.................................................................................................. 43
7 References................................................................................................................................... 50
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Liberia Environmental Vulnerability Mapping
Acronyms
Acronym MeaningCGIAR Consultative Group on International Agricultural ResearchCI Conservation InternationalDCW Digital Chart of the WorldIDP Internally Displaced PersonsFRAME Framework for Assessing, Monitoring and Evaluating the Environment
in Refugee-related Operations
FRM Foret Ressources ManagementGIS Geographical Information SystemsHIC Humanitarian Information Centre, Liberia,
http://www.humanitarianinfo.org/liberia/MEA Millennium Ecosystem AssessmentNHM Natural History Museum, LondonSRTM Shuttle Radar Topography MissionUNHCR United Nations High Commissioner for RefugeesUNEP United Nations Environment ProgrammeWB World Bank
ii
Liberia Environmental Vulnerability Mapping
iii
Foreword This report was compiled as part of UNEP’s work on the environmental considerations of human displacement in Liberia. Within a broader project entitled ‘Strengthening Capacities for the Integration of the Environmental Dimension in Refugee and IDP Settlements and Flows in Angola, Liberia and Sierra Leone’, The Liberia work included a basic needs assessments and a review of existing literature, two capacity building workshops and the publication of UNEP’s Environmental Considerations of Human Displacement in Liberia: A Guide for decision makers and practitioners. The project was undertaken with financial assistance from the governments of Norway and Sweden. The environmental implications arising from refugee or IDP camps obviously depend on the context of the camps and the vulnerability of the environment around the camps. In order to assist with the appropriate siting of camps (and also of areas earmarked for organized resettlement) UNEP developed a conceptual model of environmental vulnerability in relation to camps and then used GIS to develop a spatial model that predicts both the location of potential impacts and their likely magnitude. This vulnerability model is based on two main sources of information: the value of the ecosystem services provided by the land at a given geographic location and the accessibility from a camp to that land as a measure of the likelihood of it being impacted. In the GIS analysis these two components (ecosystem services value and accessibility) have been combined into a single map indicating vulnerability of ecosystem services to impact from camps. The maps that were produced from this methodology were passed on to the United Nations Country Team as part of the contingency planning to deal with a potential influx of refugees from Cote d’Ivoire (in early 2006). This report provides an overview of the methodology adopted in the above process. As additional funding becomes available UNEP intends to further develop the methodology began in this report. Consequently the current report should be seen as a work in progress and future versions of the methodology will be made available at: (http://postconflict.unep.ch/liberia/displacement/). If you have any comments on this report please email them to [email protected]
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iv
Acknowledgements As noted above this report was developed within the context of UNEP’s work on the environmental considerations of human displacement in Liberia and the vulnerability mapping team included: Kay Farmer, Programme Manager, UNEP Liberia, Tim Richards, Conservation Technology Ltd, Stone, David Senior Environmental Expert, UNEP Geneva, Richard Wood, Technical Coordinator, UNEP Geneva and Grant Wroe-Street, Project Coordinator, UNEP Geneva The contribution of data and technical support provided by Margaret Hall, Humanitarian Information Centre, OCHA, Liberia is gratefully acknowledged. In addition, the following people were asked to review an earlier version of the vulnerability mapping work: Jock Baker Care International, Einar Bjorgo, UNOSAT, Tyler Christie, Conservation International, James.Kamara, UNEP, Mengesha Kebede UNHCR, Christian.Lambrechts, UNEP, Andrew Mayne, UNHCR, Valentine Ndibalema, UNHCR and Luc St-Pierre, UNHCR. We gratefully acknowledge all comments received.
Liberia Environmental Vulnerability Mapping
1 IntroductionThe ending of civil war in Liberia, the signing of the Accra Peace Agreement in 2003 and the recent
successful elections all give cause for hope for the normalisation of civil society and the opportunity
for the people of Liberia to start to rebuild their lives. However, many people remain in Internally
Displaced Persons (IDP) and Refugee camps and there continues to be the threat of refugee
influxes from neighbouring countries. Liberia is rich in natural resources and still has large, intact
natural ecosystems. These ecosystems are vulnerable, however, to degradation by threats
including direct resource exploitation by both industries and populations.
The necessary establishment of IDP and Refugee camps to meet the immediate needs of
potentially large numbers of displaced people has direct and indirect impacts on the environment.
This report describes work undertaken to map the vulnerability of the Liberian environment to the
impacts of IDP and Refugee camps on the country's natural environment.
Vulnerability implies both exposure to a threat and the potential loss of environmental assets or
value as a result of that threat. As such, Vulnerability Mapping is a task fraught with difficulties in
that the threat of new camps is not well defined or controllable and how environments can be
valued is the subject of much debate and discussion. Even areas that may have a environmental
or ecological service value that is perceived to be low can be adversely effected by over utilisation
of local resources.
This report attempts to develop a methodology that is both consistent and robust and which
provides useful practical information regarding the implications of camp location. Furthermore the
methodology should be generic and it should be possible for it to be applied elsewhere.
The location of camps is ideally determined by a combination of security, logistics, political, social
and environmental factors, consequently in this report we do not attempt to specify where camps
should be located. The UNHCR and CARE International have recently published a Framework for
Assessing, Monitoring and Evaluating the Environment in Refugee-related Operations (FRAME),
(UNHCR, 2005). This report further develops a Geographical Information System methodology for
identifying potential Refugee / IDP environmental impacts in Liberia, West Africa.
1
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1.1 DefinitionsTable 1 contains a definition of terms used throughout the report. An attempt has been made in the
text of the report to be precise with the terms used. The key term is vulnerability and a generic
definition has been adopted from Tobin and Montz (1997). This is a useful definition that can be
successfully applied to environmental vulnerability.
Table 1: Definition of Terms
Threat The possibility of a Refugee or IDP camp being sited in a given locality.
Hazard Environmental degradation caused directly or indirectly by a camp.
Vulnerability “The extent to which a community, structure, service or geographic area is likely
to be damaged or disrupted by the impact of a particular hazard.” (Tobin &
Montz 1997).
Accessibility The accessibility of a given location from a camp or camps. Accessibility does
not necessarily imply proximity as barriers and impediments exist within the
landscape.
Value An attribute of a locality; based on a value system that values one
environmental attribute above another. The environment that will be lost or
damaged.
Cost Surface, or Friction Surface
A cost surface specifies the cost, in arbitrary units, of traversing one unit distance of the landscape.
Cost Distance The accumulated cost, in cost surface units, of moving across a cost-surface from A to B.
2
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2 SummaryThe methodology can be summarised in the following 5 steps:
Table 2: Summary of Methodological Steps
Data
Preparation
Step 1 Definition of existing or potential camp locations
Step 2 Definition of land characteristics from existing sources:
• Landscape morphology and hydrology
• Land cover
Definition of
Accessibility to
the environment
from camp
locations
Step 3 • Definition of a cost-surface, based on land cover, which
defines impediments to moving across the landscape.
• Definition of a cost-distance map that estimates the cost to
move from A (camp or potential camp locations) to B (all
other locations) in cost-distance units.
• Analysis of downstream impacts of drainage concentrationDefinition of
Environmental
Value
Step 4 Definition of a measure of environmental value based on land cover,
ecological service value and protection status
Vulnerability
Mapping
Step 5 Combination of Hazard Impact Potential and Value in a Vulnerability
Model.
3
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3 Developing an Environmental Vulnerability Methodology 3.1 ContextThe context of this analysis is the environmental
impact of Refugee and Internally Displaced Persons
(IDP) Camps in Liberia. Such camps may host
sizeable populations of up to 20,000 people and may
have a significant impact on the environment of the
camp and its environs. The impact of large camps is
clearly visible by satellites from space as vegetation
cover is removed from within the camp boundaries.
Depending on whether resources, such as food,
building materials and fuel wood, are brought into the
camp a camp's population will also have an a direct
impact on the surrounding environment and,
potentially, an indirect impact downstream from the
camp. Camps are visible on this Landsat image as
white geometric areas devoid of vegetation cover.
3.2 Understanding Environmental VulnerabilityA definition of vulnerability given by Tobin & Montz (1997) states that vulnerability is:
“the extent to which a community, structure, service or geographic area is likely to be
damaged or disrupted by the impact of a particular hazard”
In the context of Refugee / IDP camps in Liberia this definition can be reiterated as follows to clarify
its meaning.
• The geographic area is the area effected by the impact of the camp, either within the camp
boundary or outside the camp, or, indirectly, downstream.
• The extent refers to degree to which the geographic area may be damaged. A measure of
the extent of damage indicates that the value of the geographic area has been reduced in
some way.1
• The likelihood of damage refers to the probability of the camp having a negative impact
and can be equated with the accessibility of a given area from the camp and its sensitivity
to negative impacts.
• The impact refers to the degradation or damaged caused, for example through
1 Tobin and Montz (1997) use the word extent to mean an amount of damage, not the geographical extent
of the damage.
4
Figure 1: High density of camps to the
north of Monrovia. Camps are marked
as yellow stars.
Liberia Environmental Vulnerability Mapping
unsustainable utilisation of resources.
• The hazard is the cause of the impact, in this case the siting of a camp and its population.
From the basis of this definition it is possible to construct a conceptual model of environmental
vulnerability in relation to camps and to build a spatial model, using Geographical Information
Systems (GIS), to estimate what those impacts actually are, or what they may be in a predictive
sense.
3.3 Available Data SourcesReadily available data sources for Liberia are limited. The data necessary to build a vulnerability
model are primarily concerned with accessibility and measures of environmental value.
Data Set Date DescriptionExisting camp locations
Camp locations taken from table provides by UNEP Liberia Mission
Contingency camp locations
The sites identified as potential crossing points for a possible influx from Cote d'Ivoire are those under discussion in the UN contingency planning process currently under way in Liberia. The responsibility for identifying future camp sites rests with the Government of Liberia. Contingency crossing points, way stations and camps should be considered as provisional.
Land Use 2003 / 2004
World Bank / FRM, 2004, Current State of the Forest Cover in Liberia. Visual interpretation of Landsat imagery into 11 land use classes.
Roads Various Roads data derived from the Digital Chart of the World, HIC, UNEP and manual interpretation of Landsat imagery
Terrain•Slope•Stream lines•Catchments
SRTM 90m database from the CGIAR Consortium for Spatial Information (http://srtm.csi.cgiar.org/). Various derived data sets can be calculated from this data set, such as stream lines, drainage basins, etc.
Value of ecosystem services
1997 The estimated value of 17 ecosystem services, published by Costanza et al., 1997.
Protected Areas 2005 World Database on Protected Areas, Conservation International, Liberia.
Of these data sets the land use and terrain data merit further explanation.
5
Liberia Environmental Vulnerability Mapping
3.3.1 Terrain Morphology and Derived HydrologyThe morphology of the landscape is available from Shuttle Radar Topographic Mission (SRTM)
data. These data were acquired by the NASA Space Shuttle in February 2000 using a dual radar
systems to extract terrain heights using interferometry. The data have a nominal 30m horizontal
resolution and are available in the public domain at 90m horizontal resolution and 1m vertical
resolution (< 16m vertical error). The data utilised are from the CGIAR Consortium for Spatial
Information (http://srtm.csi.cgiar.org/) which has pre-processed the data to interpolate missing
values. An evaluation of SRTM data quality, in comparison with other sources of terrain data such
as 1:50,000 topographic maps, is provided by Jarvis et al. (2004).
This data set provides a consistent and accurate terrain model at the national level. A number of
derived data layers can be generated from these data that are of use in vulnerability mapping,
including:
• Major drainage basins
• Minor drainage basins
6
Figure 2: Example of SRTM terrain data, northern Liberia. The level of detail
of the SRTM data is apparent. In this image white areas have a higher
altitude than dark areas.
Liberia Environmental Vulnerability Mapping
• Stream lines
• Flow direction
• Flow accumulation
• Hill shading
• Contours
A national Liberian SRTM data set has been compiled and cleaned to make it hydrologically
consistent – i.e. without sinks that do not drain. The derived data sets are used in place of more
traditional data such as Digital Chart of the World (DCW). In very flat areas near the coast, where
it is not possible to accurately derive stream channels using automatic techniques, the location of
the channels has been corrected to Landsat imagery.
7
Figure 3: Terrain of Liberia Figure 4: Terrain and major stream channels
Liberia Environmental Vulnerability Mapping
Other derived terrain measures, such as slope, are also utilised in the following analysis.
The derived terrain measures were compiled using HydroTools for ArcView, Schäuble, H, (2003).
8
Figure 5: Terrain and minor catchmentsTerrain Legend in
metres.
Liberia Environmental Vulnerability Mapping
3.3.2 Land CoverThe most recent land cover information for Liberia which is both consistent and that provides full
national coverage is the World Bank / Foret Ressources Management report (WB/FRM, 2004) on
the Current State of the Forest Cover in Liberia which contains a land cover map of Liberia
compiled by visual interpretation of Landsat imagery dating from 2003 and 2004. The map was
digitised at a nominal scale of 1:100,000 with a minimum mapping unit of 1,000 ha.
These authors define a land cover classification for mapping forest cover consisting of the following
land cover classes:
Table 3: World Bank / FRM Land Cover Classes
Class No Class1 Urban (both urban and rural settlements)
2.1 Predominantly rural agricultural domain2.2 Agricultural area with small forest presence2.3 Mixed agriculture and forest3.1 Agriculture degraded forest3.2 Open dense forest3.3 Closed dense forest5 Free water6 Savannah or bare soil7 Coastal (littoral) ecosystem complex8 Agro-industrial plantation
These classes are represented in the map illustrated in Figure 6. The map covers all of Liberia
and is the most recent and consistent land cover map of the country. The map was produced for
the purpose of assessing forest cover in Liberia and is also useful for the purposes of
environmental vulnerability mapping. However, it is not ideal and it is likely that both the land cover
classification and the minimum mapping scale could be adjusted to produce a map more directly
relevant to vulnerability mapping related to IDP / Refugee camps.
9
Liberia Environmental Vulnerability Mapping
10
Figure 6: World Band / FRM Land Cover Map of Liberia, 2004 (Source HIC 2004)
Liberia Environmental Vulnerability Mapping
3.4 A Simple Model of Environmental VulnerabilityBased on the definition of vulnerability, see Table 1, the vulnerability model is based on two
information dimensions – 1) the extent or degree of loss at a given geographic location and 2) the
likelihood of a geographic area being impacted – related to the accessibility from a camp to that
location. The model is extended further later in this report through comparison with water
catchments.
3.4.1 Likelihood of Impact – Proximity and AccessibilityThe likelihood of a geographic area being damaged or disrupted by the impact of a camp is
proportional to its proximity to a camp and the accessibility from a camp to the geographic area.
Proximity does not necessarily imply accessibility. In principle an area that is close to a camp is
more likely to be impacted than an area far away from a camp, however, even if a geographic area
is in close proximity to a camp it may not be possible to access the area because of an impediment
in the landscape such as an impassable river.
In this example location B is accessible from camp A but
location C is not directly accessible because of a river
barrier, even though B and C are roughly the same distance
from the camp (have the same proximity). To get to C from A
it is necessary to cross the river by the bridge at D which
involves a journey of approximately twice the distance as to
get to B.
Rather than using the distance “as the crow flies” (Euclidian
Distance) from A to C it is more useful to use the Cost-
Distance or the estimated cost involved in getting from A to B
or C. The Cost-Distance can be calculated by assigning
costs (frictions) to land cover types according to the ease of
traversing them. For example it is easy to travel along a road
whereas it is very difficult, or even impossible, to cross the
river. However it is possible to cross the river on a road, i.e.
over a bridge.
The Cost-Distance from all of the camps illustrates how this
concept can be used to estimate accessibility from one point
(or many) to any other according to the ease or difficulty with
which it is possible to traverse the landscape. In this
illustration short cost-distances are shown in light tones
whereas long cost-distances are shown in dark tones. The
cost to get from A to C is approximately twice the cost to get
11
A
BC
Liberia Environmental Vulnerability Mapping
from A to B.
Cost-Distance is a term used in the GIS community and may imply an economic cost
in monetary units. If a person is driving a car then there are standard monetary costs
that can be applied for driving a given distance – fuel consumption, depreciation, etc.
However, the cost does not have to be represented in monetary terms and can also be
thought of as the amount of effort or energy needed to move around. This is more
appropriate if a person is walking, as most IDP / Refugee camp inhabitants are likely to
be doing.
To calculate Cost-Distance it is necessary to start with a Cost map that estimates the relative costs
necessary to traverse the landscape. A set of six classes has been used that categorises the cost
of movement a unit distance from Very Easy (low cost) to Impossible (very high cost).
Table 4: Relative Costs to Traverse a Unit Distance
Weight Movement Category1 Very Easy2 Easy3 Not Easy4 Hard5 Very Hard
100 Impossible
By relating the cost of movement across the landscape to land cover classes it is possible to
compile a travel Cost Map2. In turn this can be used to calculate Cost-Distances between points or
areas of interest.
The road network is used to define road surfaces that can be crossed with a unit cost, i.e. 1. The
river network, derived from the SRTM data, is used to define rivers that are impossible to be
crossed, other than by a bridge. For this purpose the river network was extracted using a flow
accumulation threshold of 10,000 pixels to extract only the major rivers. In this way minor rivers
and streams were excluded. The costs assigned to traversing the landscape are shown in Table 2.
2 Cost Values are also known as Friction Values
12
Liberia Environmental Vulnerability Mapping
The cost units are arbitrary and defined as 1 cost unit to traverse 92m along a road3.
Table 5: Landscape Traversal Cost Values
Class No Class1 Urban (both urban and rural
settlements)2
2.1 Predominantly rural agricultural domain
2
2.2 Agricultural area with small forest presence
3
2.3 Mixed agriculture and forest 33.1 Agriculture degraded forest 33.2 Open dense forest 43.3 Closed dense forest 55 Free water 1006 Savannah or bare soil 17 Coastal (littoral) ecosystem
complex5
8 Agro-industrial plantation 2
3 92m is the horizontal spatial resolution of the SRTM data.
13
Figure 7: Cost Surface indicating the ease of traversing the landscape relative to walking on a road.
Liberia Environmental Vulnerability Mapping
Farrow and Nelson (2001) provide a review and tools for accessibility modelling4.
The more detailed the spatial information available the better the cost-distance measure will model
the actual movement of people.
3.4.2 Extent – Degree of Loss of ValueTo measure the extent to which a geographic area may be effected by the impacts of a camp
presupposes 1) a value system that attributes worth to the area's environment and 2) the ability to
measure the degree of loss or degradation compared either to itself or to another area. Valuing the
environment is a complex and potentially contentious issue which is difficult to resolve. However, to
assess vulnerability and the associated extent or potential degree of loss of value it is necessary to
base our analysis on fixed assumptions of ecosystem service value.
Concepts of value, value systems and valuation have a long history, dating back to Aristotle, and
having meaning in a variety of disciplines (Farber et al. 2005). Conventional economic theory has
generally undervalued or even ignored environmental and ecological service values (Chichilnisky,
1996). As the Earth's natural capital is being expended the issue of ecological valuation has come
to the fore and is now an active area of research. In particular the Millennium Ecosystem
Assessment (MEA, 2005) has recently made much use of the concepts of ecosystem valuation in
the context of ecosystems and human well-being (MEA, 2005).
MEA presents the framework of Total Economic Value (TEV) after Pearce and Warford (1993), as
shown in Figure 9. In this framework TEV is comprised of Use Value, including Direct Use Value,
Indirect Use Value and Option Value, and Non-Use or Existence Value.
4 Note that software tools have been developed for this specific study and Farrow and Nelson's tools have
not been utilised.
14
Figure 8: Cost Surface Detail
Liberia Environmental Vulnerability Mapping
• Direct use values are ecosystem services used for both consumptive and non-consumptive
purposes.
• Indirect use values are intermediate inputs for final goods and services, such as water, soil
nutrients, control services, etc.
• Option values are values attributed to the option of utilising the ecosystem in the future.
(Source MEA, 2005)
The transformation of land cover from one type to another (or one ecosystem to another) involves
a corresponding change in value. Figure 10 illustrates the value changes involved in deforestation.
15
Figure 9: Total Use Value (Source: MEA, 2005)
Liberia Environmental Vulnerability Mapping
As indicated above - in developing an environmental vulnerability map it is necessary to assess the
extent, or amount, of potential damage and associated potential conversion from one ecosystem to
another. This implies both that the value of the geographic area is known, or that it is known
relative to another geographic area, and that the value system defining the valuation is also known.
This challenge must be confronted in order to produce a measure of vulnerability that is more than
just a statement of accessibility.
Knowledge of accessibility to an area is not sufficient to make a judgement as to whether that area
is more or less vulnerable than another equally accessible area. The second component of our
vulnerability model is a measure of environmental value in order to make this judgement. Costanza
et al. (1997) state that “although ecosystem valuation is certainly difficult and fraught with
uncertainties, one choice we do not have is whether or not to do it”. These authors have taken on
this task and have estimated the economic value of 17 ecosystems services based on a synthesis
of results from more that 100 separate studies. The 17 ecosystem services considered are shown
in Table 6 and their estimated values are given in Table 7.
16
Figure 10: Ecosystem Conversion (Source: MEA, 2005)
Liberia Environmental Vulnerability Mapping
Table 6: Ecosystem Services and Function (Source Costanza et al. 1997)
No Ecosystem Service
Ecosystem Functions
1 Gas regulation Regulation of atmospheric chemical composition
2 Climate regulation Regulation of global temperature, precipitation, and other biological mediated climatic processes at global or local levels
3 Disturbance regulation
Capacitance, damping and integrity of ecosystem response to environmental fluctuations
4 Water regulation Regulation of hydrological flows
5 Water supply Storage and retention of water
6 Erosion control and sediment retention
Retention of soil within an ecosystem
7 Soil formation Soil formation processes
8 Nutrient cycling Storage, internal cycling, processing and acquisition of nutrients
9 Waste treatment Recovery of mobile nutrients and removal or breakdown of excess or xenic nutrients and compounds
10 Pollination Movement of floral gametes
11 Biological control Trophic-dynamic regulations of populations
12 Refugia Habitat for resident and transient populations
13 Food production That portion of gross primary production extractable as food
14 Raw materials That portion of gross primary production extractable as raw materials
15 Genetic resources Sources of unique biological materials and products
16 Recreation Providing opportunities for recreational activities
17 Cultural Providing opportunities for non-commercial uses
(Source Costanza et al. 1997)
Table 7: Average Global Value of Annual Ecosystem Services
Ecosystem Annual Local Value (US$/ha/year, 1994 values)
Coastal 4,052
Open Ocean 252
Wetlands 14,785
Tropical Forest 2,007
Lakes, Rivers 8,498
Temperate/Boreal Forest 302
Grasslands 232
Cropland 92
Estuaries 22,832
Tidal marsh / mangrove 9,990
Swamps / floodplains 19,580
(Source Costanza et al. 1997)
17
Liberia Environmental Vulnerability Mapping
The ecosystem service values given in Table 7, together with the World Bank land cover maps
described below, are used as the basis of a Liberian ecosystem valuation system as an input to the
vulnerability assessment. The land cover map is used to spatialise the values of the ecosystem
services.
There are differences of opinion as to the monetary value of ecosystems (Costanza et al., 1997,
Pimentel 1997), however the valuation can be used as relative indicators of their value and provide
an objective way of compiling an environmental value map of Liberia.
The values given for each ecosystem are in US$ per hectare per year. The WB/FRM land cover
classification is shown in Table 8 together with more convenient normalised annual local values.
As there is not yet consensus about the precise monetary value of ecosystem services and that in
creating the vulnerability map it is not necessary to assign absolute values in monetary terms to
the land cover classes, relative weights have been used instead.
The WB/FRM classification has more sub-classes per ecosystem than Costanza (1997) and
estimated values are given for these classes are given below in Table 8.
Table 8. Land Cover Class Environmental Value Weights
Land Cover Class Value WeightUrban 1Predominantly rural agricultural domain 8Agricultural area with small forest
presence
10
Mixed agriculture and forest 33Agriculture degraded forest 50Open dense forest 50Closed dense forest 66Free water 281Savannah or bare soil 8Coastal ecosystem complex 134Wetlands 489Agro-industrial plantation 28
(Shaded land cover classes indicate those that are considered to be natural and
whose values are increased by also being located in current or proposed
protected areas.)
The land cover classes of the WB/FRM map are assigned these values on a per pixel basis,
resulting in a map of the relative ecosystem service values provided by each land cover class.
Note that the analysis has been undertaken at the spatial resolution of the SRTM data which is
nominally 92 m, or 0.85 hectares.
18
Liberia Environmental Vulnerability Mapping
There is currently much debate about the need to include the value of ecosystem services in policy
and planning decision making, however, there is as yet little published information to go on, in
Liberia and elsewhere. As ecological services values for Liberia were not available to the authors
the values published by Costanza et al. (1997) have been used instead. With this in mind the
valuation has been used as an indicator of the relative values of ecosystem services rather than as
an absolute measure of their values in monetary units.
The task of ecological valuation in respect of environmental vulnerability mapping is further
complicated by issues of scale. At the national level Liberia is rich in natural resources and has a
range of ecosystems that provide high value services to society. However, at the scale of the IDP
or refugee camp only a limited range of the national ecosystem spectrum is likely to be present
locally. It follows that only a limited range of ecosystem services may be available at the camp level
and that what may seem a low value environment within the national context is actually a high
value environment in the local context. In this report the terms “lower-value” and “higher-value” are
used in terms of the national spectrum of ecosystem service values . As we have seen what may
be termed “lower-value” at the national scale could be termed “higher-value” at the local scale,
however this distinction is not generally made in the text.
It should also be noted that whilst Liberia is rich in ecosystems, society is poor and needs to
develop economically, and cannot necessarily afford to forego converting some natural ecosystems
into more economic forms of production including IDP and Refugee camps. There is therefore a
trade-off to be made between retaining the “value” of natural ecosystems, and the services they
provide, and the benefits of converting the ecosystem to another use. Informed planning decisions
must balance this trade-off of values. Uninformed planning, or the absence of planning altogether,
can lead to the spectre of a third alternative where ecosystem degradation is such that the
environment can support neither ecosystem services nor economic activity. The objective of the
vulnerability mapping is to highlight those areas where the trade-off, or loss of value, is
disproportionally high with respect to IDP and Refugee camps.
19
Liberia Environmental Vulnerability Mapping
3.5 Protected AreasFurther information pertaining to the perceived value of the land cover classes is available in the
form of the location of established and proposed protected areas and biodiversity priority zones.
These maps indicate areas that have been identified as being of high value for the conservation of
natural resources and have been developed primarily by Conservation International and the
Natural History Museum of London (NHM).
These protected area maps are incorporated into the analysis by doubling the ecosystem service
value weights inside the protected areas for those classes that represent natural ecosystems, i.e.
excluding agriculture, degraded forest, industrial plantations and urban areas.
The protected areas used are those listed by WB/FRM (2004), namely:
Existing Protected Areas
• Sapo National Park
• East Nimba Nature Reserve
Proposed Protected Areas
• Lake Piso
• Lofa-Mano
• Wologizi East
• Wonegizi West
• West Nimba
• Cesto-Gbi
• Cestos-Sehnkwekn
• Grebo
• Marshall
Existing and proposed protected areas are given equal weight. The biodiversity priority areas maps
has not been utilised because it is very correlated with the protected areas data and has very
general boundaries. Also the National Forest areas are not given any additional value weight.
3.6 Ecosystem Service Value Map The Ecosystem Service Value Map is shown in Figure 12. Areas are valued according to Table 8
and coloured according to the vulnerability classification described below. Areas are coloured with
increasing value from cyan (values 0 to 50), through magenta (values 51 to 100), to red (101 to
150) and lastly green (151 and above). From Table 8 it can be seen that cyan covers mainly
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Figure 11: Protected Areas (green) &
Proposed Protected Areas (cyan)
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modified ecosystems such as agriculture, magenta covers mainly natural undisturbed ecosystems
such as closed dense forest and red covers protected undisturbed ecosystems. Very high values,
shown in green, are protected wetlands.
In addition to providing an input to the vulnerability assessment the ecosystem service value map
could be used for other purposes such as estimating the value of Liberia’s ecosystems by county
or by watershed.
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Figure 12: Ecosystem Service Value Map excluding Protected Area weighting
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3.7 Combining Hazard Impact Potential and Value in a Vulnerability ModelTo complete the Environmental Vulnerability Map the Cost-Distance and Ecosystem Service Value
maps must be combined to show the range of combinations of potential exposure to the hazard
and ecosystem service values.
Plotted on a graph it is clear to see that at the four corners:
• A – has high ecological service value and is near to a camp
• B – has high ecological service value and is far from a camp
• C – has low ecological service value and is far from a camp
• D – has low ecological service value and is near to a camp
The corner that is most vulnerable is A. The corner that is least vulnerable is C. The line from C to
A represents an axis of increasing environmental vulnerability.
The vulnerability colour key colours the vulnerability axis from green (C) through cyan, blue
and magenta to red (A).
At right-angles to the vulnerability axis is an axis of equal vulnerability. For example, a line from D to B represents areas that have medium vulnerability. Areas that have very low ecological service
value and that are near a camp (D) have a medium level environmental vulnerability; as do areas
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Figure 13: Vulnerability Model
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that have very high ecological service value but which are very far from a camp (B). In the colour
key all values along this line have the same colour (blue) but the shade of the colour changes from
dark blue at D to light blue at B. The complete colour key is shown below in Figure 14 and covers
all possible combinations of the data.
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Figure 14: Vulnerability Model - vulnerability axis and
equal vulnerability zones 1 - 8
Figure 15: Vulnerability Model
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3.7.1 Interpreting the Vulnerability MapThe colour table in Figure 15 may seem rather abstract, however, with the aid of an example it is
quite simple to interpret.
This example shows a camp in an agricultural zone with
low forest presence and that has a relatively low ecological
services values. The camp is located at the red dot at the
centre of the vulnerability zone. Near the camp the
vulnerability map is dark blue, indicating a medium level of
vulnerability with low ecological service values near the
camp. Further away from the camp the vulnerability map is
green, indicating low ecological service values that are far
from the camp and which have a low vulnerability rating.
The colour table should be used to interpret the
vulnerability classes. The greener the colour is the lower
the vulnerability; the redder the colour is the greater the
vulnerability.
This example is in an environment of mixed agriculture and
forest, and closed dense forest. There are no green areas
and the blues, cyans and magenta tones indicate medium
to high vulnerability ratings.
Note that low ecological service value does not mean no ecological service value, just that it is
lower than the other categories.
As mentioned above protected areas are another source of information relating to the perceived
value of an area. Protected areas may be located where they are for a range of reasons, but they
generally contain features that are highly valued for other than economic reasons, such as
biodiversity, aesthetic value, etc. They are given additional weight in the vulnerability analysis by
multiplying their ecological service values by a factor of two. In the vulnerability map the high
ecological service values are generally associated with either protected ecosystems or wetlands.
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3.7.2 Vulnerability Map ExamplesThe environs of Monrovia have a dense
concentration of existing IDP and Refugee camps,
both around the city and strung out to the north east
along the road to Gbarnga. To the north of the city
and the St Paul river there are nine camps within a
radius of just 4 kilometres, constrained on three
sides by the sea to the west, the St Paul river to the
south and another smaller river to the north. The
other camps are quite evenly spread along the road
between 4 and 10 kilometres apart.
The close proximity of these camps means that there is an extensive contiguous vulnerability zone
stretching from the coast for about 120 kilometres inland. This zone passes through rural
agricultural areas and an extensive area of industrial plantation. Near Gbarnga it also skirts around
areas of mixed agriculture and forest.
The map on the following page shows the vulnerability map superimposed on top of the land cover,
together with the existing camps. The vulnerability zones range from low vulnerability in green,
through medium vulnerability areas in blues, to some small areas of higher vulnerability in magenta
and red.
In this part of the country the highest ecosystem service values are found along the coast. The
Buchanan IDP camp is the only camp located in isolation in the south east of the map. This camp
is in close proximity to a coastal area of high ecosystem service values that is coloured red and
classed as highly vulnerable.
What may not be immediately apparent from the vulnerability map, but which can be seen from the
river network, is the fact that 15 of the existing camps are upstream of the proposed Marshall
protected area located on the coast.
This map illustrates the point that in order to minimise environmental impacts camps should ideally
be well spaced in the landscape to prevent their environmental footprints converging and imposing
increased environmental pressures. Furthermore, attention should be paid to the location of camps
within the drainage network as impacts may be off site, particularly where drainage networks may
converge.
Figure 17 shows an example vulnerability map from the north east of Liberia, containing the five
contingency planning sites at B'hai Niko, Bin Sawmill, Janzon Town, Zleh Town and Pohan.
25
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26
Figure 16: Vulnerability Map of the environs of Monrovia
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In contrast to the previous example these sites have
been identified as possible sites in contingency
planning and as yet are not yet in use. The eastern
part of the country is more forested and as a
consequence has higher ecosystem service values
that the previous example. Furthermore, the sites
are in the vicinity of the proposed Zwedru protected
area. The Zleh, Pohan and B'hai Niko sites are all
located in small agricultural areas, whereas Bin
Sawmill and Janzon Town within either open or
closed dense forest.
Compared with the previous map there are few low vulnerability areas in green and more areas of
cyan, magenta and red, indicating higher environmental vulnerability. This is a direct consequence
of the higher ecosystem service values of this generally forested region. Along roads and where
the land cover is more open the vulnerability zones spread out over a wider area, in particular
around Pohan and Zleh.
The Bin Sawmill site is located in close proximity to the proposed Zwedru protected area. The
medium to high vulnerability immediately surrounding the site becomes high vulnerability within the
boundary of the proposed protected area. Note that the road network enables accessibility into the
proposed protected area from both the north-west and from the south. This combination of close
proximity of contingency sites to the proposed protected area and the existence of roads means
that the protected area is vulnerable to encroachments and related environmental impacts.
The Janzon Town contingency site shows high vulnerability in its immediate vicinity because of its
location within closed dense forest. Other sites exist nearby, for example the area of rural
agriculture to the north east of the Janzon Town vulnerability zone, that may be more suitable from
an environmental perspective for the location of a contingency site.
Of these sites, Pohan and Zleh Town have generally lower environmental vulnerability and may be
prioritised ahead of the other more vulnerable sites.
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Figure 17: Vulnerability map of contingency sites in eastern Liberia
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4 Running the ModelTo calculate the Cost Distance it is necessary to have a starting point and and end point. The
starting point is the camp(s) locations(s) and the end point is every other geographic location. With
regard to camp location there are three possible scenarios for which the model can be run, namely
using:
• The location of existing camps
• The location of zones for camp locations that satisfy the UNHCR FRAME criteria
• The location of camps identified as part of contingency planning for future population
displacements
Clearly the vulnerability model is dependent upon the location of refugee / IDP camps because by
default an absence of camps means an absence of vulnerability5. This means that there is no
unique vulnerability map that can be made. All vulnerability maps must be in response to an
identified threat – or distribution of camps.
4.1 Step 1 – Data Preparation - Camp LocationsFor the analysis camp locations may be either:
• Existing camps
• Potential locations for new camps using a camp location methodology such as UNHCR-
FRAME
• Potential zone locations for new camps based on contingency planning
Any of these, or combinations of these, can be used as a starting point for the analysis.
In this example the location of existing camps, crossing points and way points are used to seed the
vulnerability model.
5 In the absence of a camp a geographic area may, of course, be vulnerable to some other type of threat.
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Figure 18, above, shows the location of existing IDP and Refugee camps in Liberia. These camps
can be used as an input to the vulnerability model.
Figure 19 outlines the UNHCR-FRAME approach, the last frame showing the potential locations for
camps in green. Note that existing known sites are included in this analysis and are therefore
shown as being unsuitable for further camp development.
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Figure 18: Location of Existing Camps and Contingency Sites
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Figure 19: UNHCR FRAME Site Selection Approach
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4.2 Step 2 - Definition of Land Characteristics from Existing SourcesLand cover and terrain data should be prepared as describe in the previous sections in order to
generate cost-surface and ecological service value maps.
4.3 Step 3 – Calculating Proximity and AccessibilityGiven a set of camp locations, or potential camp location zones, it is possible to calculate the Cost-
Distance from the camps to all other locations, using the camp locations and Cost-Surface
described in Section 3.4.1 and illustrated in Figure 7.
Figure 20 shows the Cost-Distance of moving across the landscape from existing camps.
The influence of a camp is obviously localised and calculation of the cost-distance from a camp to
every location in Liberia is of limited use because camp inhabitants will have a local rather than
national impact. The cost-distance should therefore be limited to the immediate vicinity of the
camp(s). The FRAME methodology uses a threshold of 15 km (15,000m) as the distance that
camp members are likely to walk in a day.
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Figure 20: Cost-Distance base on existing camps, contingency sites and crossing points,
blue = higher cost, yellow = lower cost
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Figure 21 illustrates the cost-distance surface within 15k cost-distance units of the existing camps.
The pattern is clearly highly influenced by the road network and reflects that the ease of traversing
the landscape by road.
The low cost-distance values at location A and B, in Figure 22, illustrates that the barrier of the
rivers means that movement from camps on the south side of the river is forced to go the long way
around over the bridge, making the blue area at A and B relatively inaccessible from the camps on
both the north and south sides of the river.
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Figure 21: Cost-Distance from camps < 15,000 cost-distance units
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34
Figure 22: Detail of cost-distance analysis around Monrovia.
A
B
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4.4 Step 4 – Definition of Environmental Value – Dimension 2Figure 24 shows a detail of the environmental value for the same area shown in Figure 22, the
boundary of the 15k cost-distance threshold is also shown. It is quite clear that the existing camps
are generally located in areas of low ecological service value.
Despite the existing camps generally being located in an area of relatively low ecosystem service
value this does not imply that they are in an area that has no ecosystem service value. These
relatively low values must be seen in the context that Liberia contains some areas of very high
value, such as intact tropical forest habitats.
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Figure 23: Ecosystem Service Value in relation to 15k cost-distance footprint
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4.5 Step 5 Combining Hazard Impact Potential and Value in a Vulnerability ModelTo complete the Environmental Vulnerability Map the cost surface and ecosystem service value
maps must be combined to show those areas that are a) potentially exposed to the hazard and b) have a high ecosystem service value. This is done by subdividing the two dimensional data space
into a matrix and colour coding the vulnerability map according to which cell in the matrix a pixel's
values occupy in the data space.
Figure 24 shows the vulnerability of the environment to existing camps. Please refer to Figure 13
for a full explanation of the colour coding. Cyan tones indicate low ecological service values with
increasing proximity to a camp from light to dark tones. Similarly orange and red tones indicate
high environmental values with increasing proximity to camps from light to dark tones. It is clear
from Figure 24 that existing camps are located in a region of generally low ecological service
values, except near the coast. It should, however, be noted that low ecological service values does
not mean no ecological service value.
Figure 25 shows the environmental vulnerability map for the entire country based on existing
camps and also the contingency sites and entry points identified in relation to a potential influx of
refugees from Cote D'Ivoire. The spatial distribution of vulnerability intensity is apparent from the
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Figure 24: Vulnerability of the environment to existing camps in the environs of Monrovia
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distribution of colours.
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Figure 25: Vulnerability of the environment to existing camps and contingency sites and entry
points
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5 Drainage and Catchment AnalysisWater catchments provide a subdivision of the landscape into units that have a physical basis and
which are closely associated with hydrological processes and which are directly affected by land
management and land cover changes. In the landscape a hierarchy of drainage catchments exists
from major drainage basins to micro-catchments.
The SRTM terrain data provides a consistent information layer from which a number of drainage
parameters can be extracted. HydroTools for ArcView has been used to correct the SRTM data to
remove sinks that have no drainage outlet, which then enables the stream network and
catchments to be extracted. A number of derived hydrologic measures can be extracted from the
SRTM data including:
• flow direction – the direction of flow from a cell
• flow accumulation – the total accumulation of flow into a grid
• flow length – the distance from the farthest upstream point in a catchment
• catchments / watersheds – contributing area
• stream order - the numerical order of a stream branch in the stream network
• stream network – the network of stream channels
Using these derived measures the a set of catchments and the drainage relationships between
them can be calculated. Catchments can be identified at different levels in the national catchment
hierarchy. For the purposes of this study a threshold of 1,000 cells (approximately 1,000 ha) was
used to define the number of contributing cells to identify a stream, which in turn defines the size of
catchment extracted. Figures 26 and 27 show the stream network6 and the associated
catchments.
6 Figure 26 shows both the major and minor stream networks calculated using 10,000 and 1,000
contributing cells respectively.
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39
Figure 26: Major and minor stream network
derived from SRTM data
Figure 27: Minor catchments extracted from SRTM data
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The model outlined in previous sections uses per-pixel values of accessibility and ecosystem
service value to define a two dimensional data space which is subdivided into vulnerability classes.
The catchment maps however are a type of isopleth map and identifies contiguous areas with the
same arbitrary value (catchment id) and cannot easily be considered as an additional data axis in
the model. The following section considers how the catchment and drainage information derived
from the SRTM data can add value to the vulnerability model.
5.1 Ecological Service Value by CatchmentFigure 12 shows the ecological service value map, constructed through the combination of the
FRM land cover map and Costanza's ecological service value table. In Figure 12 the value of a
patch of landscape is governed by the ecosystem boundaries, many of which are artificially
imposed on the landcape by anthropogenic modification of the natural land cover, for example the
boundary between closed dense forest and open dense forest is a function of logging intensity.
Catchments however provide a natural subdivision of the landscape that are directly associated
with landscape morphology, hydrological processes and land cover.
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Figure 28: Ecological service value by catchment (protected area weighting not included)
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Within each catchment the sum of the ecological service value, according to Figure 12, has been
calculated and is shown in Figure 28. The general division of the country into north-western,
central and south-eastern zones is apparent, although this is also clear from the basic land cover
map. Where this map is useful is in identifying high value catchments that are intact and,
conversely, lower value catchments where camps may be more suitably located – in particular in
the north-west and the south-east of the country. The catchment value and the land cover maps
should be viewed together rather than individually to get the maximum benefit from them both.
The location of camps in lower value catchments may reduce the absolute impact on the
environment, however, higher value downstream catchments may be indirectly affected.
5.2 Drainage ConcentrationThe downstream impacts of pollution from camps can be estimated by looking at the drainage
catchments in which camps occur. For example, of the 37 known existing camps in the vicinity of
Monrovia, 15 of them, with existing populations totalling 100,895 people, are upstream of a single
outfall on the coast, illustrated by “B” in Figure 29.
The pollution of watercourses near a camp will only result in contamination of the watercourse
downstream and not upstream. Because the drainage from micro catchments contributes to larger
drainage basins there is the possibility that pollution from a number of camps will concentrate to a
single point, even if the camps are apparently well distributed in the landscape. Where stream
channels are well defined, contamination of the watercourse will be confined and will effect only the
channel (its water quality, flora and fauna) and not the surrounding area. However, where the
channel is less well defined, or where the stream flows into a wetland or lake, the contamination
41
Figure 29: Drainage of 15 camps to single outfall
at B.
B
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will be dispersed more widely. A procedure is being developed to add the downstream impacts of
pollution to the vulnerability analysis. Note that in some parts of the country the pollution of
watercourses could have cross border implications.
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6 Cartographic Vulnerability MapsThe plates on the following pages illustrate the vulnerability mapping applied to the ecological
service value and accessibility maps described in the preceding sections. The Plates show the
vulnerability analysis run on the known existing IDP and Refugee camps and potential camp and
transit camps identified in contingency planning in early 2006. The existing camps are mostly in the
environs of Monrovia, whilst the contingency planning camps are generally in the east and north of
the country. Please refer to the key to the Vulnerability legend shown in Figure 13 for an
explanation of the colours.
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44
45
46
47
48
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7 ReferencesChichilnisky, G., 1996, The economic value of the Earth's resources, Trends in Ecology and
Evolution, 11:3 135-140.
Costanza, R., d'Arge, R., de Gros, R., Faber, S., 1997, The value of the world's ecosystem
services and natural capital. Nature 387: 253-260.
Farrow, A., Nelson, A, 2001, Accessibility modelling in ArcView 3 – An extension for computing
travel time and market catchment information, International Centre for Tropical Agriculture.
Farber, S., Costanza, R., Wilson, A., 2005, Economic and ecological concepts for valuing
ecosystem services, In Environmental Values, Kalof, L., Satterfield, T. (Eds).
Foret Ressources Management, June 2004, Current state of the forest cover in Liberia – forest
information critical to decision making, Report to the World Bank
Jarvis, A., Rubiano, J. , Nelson, A., Farrow, A., Mulligan, M, 2004, Practical use of SRTM data in
the tropics – Comparisons with digital elevation models generated from cartographic data, Centro
Internacional de Agricultura Tropical (CIAT), Working Document No 198, 32p.
http://srtm.csi.cgiar.org/PDF/Jarvis4.pdf
Millenium Ecosystem Assessment, 2005, Ecosystems and human well-being: a framework for
assessment
Natural History Museum, 2005, Measuring Biodiversity Value, www.nhm.ac.uk
Pearce and Warford (1993), World Without End: Economics, Environment, and Sustainable
Development, Oxford University Press.
Primack, R., Essentials of Conservation Biology, 1998, Sinauer Associates
Pimentel, D, Wilson, C., McCallum, C., 1997, Economic and environmental benefits of diversity,
BioScience 47: 747-757.
National Research Council, 2005, Valuing ecosystem services – towards better environmental
decision-making, National Academies Press, Washington DC
Schäuble, H., 2003, HydroTools 1.0 for ArcView 3.x, Institute of Applied Geosciences, Technical
University of Darmstadt, www.terracs.de
Tobin, G.A., Montz, B.E., 1997, Natural Hazards, Explanation and Integration, The Guildford Press,
New York, London
UNHCR, CARE International, 2005, Geographic Information System (GIS) Applications for
Environmental Management in Refugee-related Operations, UNHCR.