EO Information Services in support of Multi-Hazard …siteresources.worldbank.org/EXTEOFD/Resources/84267… · · 2012-05-10Multi-Hazard Vulnerability Assessment in Yogyakarta

Date : 21 February 2012

EO Information Services in support of

Multi-Hazard Vulnerability Assessment in Yogyakarta (Indonesia)

F. N. Koudogbo and A. Arnaud Altamira Information

I. Bauwens, H. Tambuyzer Eurosense

Agenda

Introduction – Context of the project

– Delivered EO information products / services

– EO products methodologies

The EO Information main Services – Urban mapping product of infrastructure and building inventories

– Historical mapping of terrain deformations

The EO Information Additional Services – Precise Digital Elevation Model (DEM)

– Multi-hazard vulnerability mapping

– Flood Risk Analysis

Conclusion & User Feedback – Advantages / Constraints & Recommendations

– User Feedback Assessment

Delivered EO information Products/Services

Objectives of the project:

Delivered EO Information services:

Service 1: Urban mapping product of infrastructure and building inventories

Service 2: Historical mapping of terrain deformations

Additional Desirable Information 1: Precise Digital Elevation Model (DEM)

Additional Desirable Information 2: Multi-hazard vulnerability mapping concerning the risks of climate and disaster impacts

Additional Desirable Information 3: Flood Risk Analysis: Flood Hazard Map + Flood Hazard Impact

Need for up-to-date information on urban mapping and land subsidence – Multi-Hazard vulnerability assessment for assigning metrics that will help

in the definition of the Multi-Hazard City Risk Index (MHCRI)

EO Information Services in support of EO Support for Multi-Hazard Vulnerability Assessment

in Yogyakarta (Indonesia)

All delivered GIS files have been integrated in the World Bank GIS system

EO information Products Methodologies Generation of Service 1 outputs

Urban map: location of urban infrastructure

The urban map is created for the centre of Yogyakarta and surroundings.

Source data

SPOT5, 2.5m

Open source ancillary data (Open Street Map, Google Earth, Bing maps, Wikimapia)

Terrain and building height information

Format GIS compatible vector layer

Scale 1:10.000

MMU 0,25 (urban area) – 0,5 ha (rural area)

MMW 10 m

Area produced 700 km²

Reference date 2008-05-18

Accuracy Thematic: 90% - Geometric: < 2.5 m

Urban mapping product of infrastructure and building inventories

© Spot Image S.A.,2011. All rights reserved

False color infrared of the total mapped area extracted from the SPOT5 scenes, acquisition date 2008-05-18.


EO imagery Ancillary data -OSM -Wikimapia -Google Earth -BingMaps

Sealing layer Prelim. urban map

urban map

Calculation urban densities

Preprocessing Preprocessing

• Manual delineation & interpretation

• GIS processing • Legend conversion

Points & lines

EO information Products Methodologies Legend Conversion

Conversion Urban Atlas legend to the Mutli-Hazard City Risk Index (MHCRI) legend

Original code

Urban Atlas map

* Classes in grey and italic are not mapped in the urban map

ERS/ENVISAT ALOS

Spatial resolution 40 m 30 m

Absolute location

accuracy Better than 10 m Better than 10 m

Relative X, Y

accuracy

Metric in both E-W

and N-S direction

Metric in both E-W

and N-S direction

Thematic accuracy 2 mm/yr 5 mm/yr

Absolute accuracy 5 mm 7 mm

1-Mar-03 29-Feb-04 28-Feb-05 28-Feb-06 28-Feb-07 28-Feb-08 27-Feb-09 27-Feb-10Mar-03 Mar-04 Mar-05 Mar-06 Mar-07 Mar-08 Mar-09 Mar-10

26-Mar-96 25-Sep-96 27-Mar-97 26-Sep-97 28-Mar-98 27-Sep-98 29-Mar-99 28-Sep-99 29-Mar-00 28-Sep-00 30-Mar-01Apr-96 Oct-96 Apr-97 Oct-97 Apr-98 Oct-98 Apr-99 Oct-99 Apr-00 Oct-00 Apr-01

29-Nov-06 30-May-07 28-Nov-07 28-May-08 26-Nov-08 27-May-09 25-Nov-09 26-May-10 24-Nov-10 25-May-11Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10 Jun-11

AOI

ERS Track 318

ENVISAT ASAR Track 318

ALOS Frame 431/7030

Historical Mapping of Terrain Deformations

Analysis of terrain deformation based on the processing of satellite data with the SPN

(Stable Point Network) software.

Developed by Altamira Information, SPN is capable to extract precise displacement and position information of the radar stable points.

− Velocity expressed in mm/yr for each measurement point

− Time series of the displacement

Three independent processing:

− 19 ERS for the period 1996-2000

− 27 ENVISAT for the period 2003-2009

− 25 ALOS PALSAR for the period 2006-2011


Data extraction: The SAR images and the acquisition parameters are extracted from the SAR data products

Data selection: Selection of the optimal images and interferometric pairs to be used for the processing

Data Coregistration: All the SAR data are resampled to the same acquisition geometry (Super Master image)

Initial selection of PS: Initial estimation of the location of the PS in the Super Master image

SPN processing: Estimation of the ground deformation and point height for each pixel of the SAR image


The SPN (Stable Point Network) processing

EO information Products Methodologies Generation of Add Des Inf 1 outputs

DEM (Digital Elevation Model)

− No suitable SPOT pair available in archive at the beginning of the project.

− Due to persistent cloud coverage, no new EO scenes were acquired in the foreseen time window no DTM, DHM and DSM could be produced.

− As an alternative a SPOT DEM was purchased. To compensate for the loss of spatial resolution and vertical accuracy, a larger area was ordered (1425 km²).

SPOT DEM:

− Extracted from SPOT 5 High Resolution Stereoscopy (HRS) data.

o The HRS instrument consists of two fixed cameras, which are inclined fore-ward and aft-ward by 20° along the ground track.

o The base-to-height ratio is 0.8. The pixel size of the HRS data on the ground is 10m x 10m.

Following layer corrections have been executed:

− Automatic filtering to eliminate correlation artifacts

− Flattening of non-running water bodies (rivers, etc… excluded) exceeding 0,5 km²

DSM grid resolution (GSD) 20 m

Vertical accuracy relative = 15m

Area produced 1425 km2

Reference period 2003 - 2011

No data value -32767

Product format raster format (GeoTIF)


Local Partner in Bandung - IWRW (Indonesia Water Resource Watch)

− Company founded in 2009.

− Strong partnership with the RCWR (Research Center for Water Resources)

Team of 4 persons involved for the project; main contact is Expert Hydrologist

Methodology based on 3 steps:

Hazard analysis

− Hazard identification based on PIP2B DIY (Yogyakarta Special Region Buildings and Settlement Information Centre) information

− Hazard maps of PIP2B are re-digitized into a GIS format

Vulnerability Assessment

− UNESCO - IHE methods*.

Risk Analysis

− Based on computed Hazard and Vulnerability indices

− Computation of the Multi-Hazard Regional Risk Index

Multi-Hazard Vulnerability Mapping

*http://unescoihefvi.free.fr/system.php#


Hazard analysis Vulnerability Assessment Risk Analysis

MHRRI because the overall Yogya province is considered.

Based on the Hazard and Vulnerability indices.

HVIMHI_SDMHRRI

Vulnerability = Exposure

+ Susceptibility – Resilience

2 components are considered.

Data source is the Central Bureau of Statistic Republic of Indonesia (BPS)

UNESCO-IHE formulas are applied

6 kinds of hazards are considered.

The Hazard information is transferred to Sub-District level applying a weighting factor for each sub-district.

EO information Products Methodologies Context for Add Des Inf 3

Mount Merapi (Gunung Merapi) region

− active strato-volcano located 28 km North of Yogyakarta

− has erupted regularly since 1548

− Thousands of people live on its flanks, with villages located up to 1,700 m above sea level.

Lahar Flood October- November 2010

− Lahar = mudflows and debris flows originating from the slopes of a volcano

− Caused by heavy rainfall events when the debris of the eruption are driven by the current (= flash flood)

− Eruption Mount Merapi (26/10/2010)

− Lahar caused by a 2 hour rainfall of 48 mm on the 29 Nov. in the Merapi top area

Flood Hazard Map (lahar simulation)

Damage Pictures on Lahar hazards and risks following the 2010 eruption of Merapi volcano

Population Density on the flanks of Merapi Volcano and Rivers Headwater © OCHA


Flood Hazard Map represents the result of a flood simulation for a past lahar event

AOI is at least 10 km buffer of Boyong & Code river over length of approx. 50 km.

FloodArea© software : a simplified 2D hydraulic model using the Manning equation

Flash Flood modelling

− Calculation volume of lahar

− Precipitation measurements in reference period (Bencana Banjir, nov 2010)

− Flow surge with a mean sediment concentration of 50% volume

− Reduction of river cross-section and higher friction parameter

Important local and expert information Volcanic Technology Development and Research Center (BPPTK)

Volcanology and Geological Disaster Mitigation Center (PVMBG)

Metereology, Climatology and Geophysics Agency (BMKG)

A rainfall intensity of 48mm in 2 hours (cfr. the rain event of 29th November 2010) at the summit of Mount Merapi

A perimeter of ashes/debris/dust of respectively 10 – 15 km

The high topography of Mount Merapi characterizing the region

The impact of sediments on roughness and viscosity influencing the flood propagation

Originating Process of Lahar Floods and Sabo Dam constructions along the river course

The Flood Hazard simulation assumptions and conditions



DTM with height information

− Spot DEM (cfr. Add Des Inf 1) & SRTM

− influence of the volcanic material on the river cross-sections

Rainstorm distribution with hydrograph

− 4 areas with different rainfall intensities.

− above 1700m - max rainfall of 48mm/h.

Roughness layer based on Land-cover data derived from EO-data

− Friction parameter “Manning coefficient” assigned to Urban Map (cfr Service 1) & Globcover2009 (© ESA 2010 and UCLouvain)

− Additional impact of sediments on roughness and flow velocity

Corrected DTM

Rainstorm intensity distribution

Roughness layer

Area affected by eruption material

© BNPB

Flood Hazard Map

Agenda











Urban Mapping Product Outputs formats & Guidelines to use

Vector files (Shapefile – UTM WGS84 zone 49 South)

− Can be used and easily updated in a GIS environment (corresponding layer files with adapted colour legend).

− Contains attribute table with different fields which give more information about each polygon (i.e. MHCRI-code at different levels and polygon area)

Digital map (.pdf & .png)

− Overview maps of urban map at scale 1/100.000 and map sheets at scale 1/10.000.

− Can be visualized with any image viewing software and printed at the specified scale.

Urban Mapping Product Outputs formats & Guidelines to use

Urban Mapping Product Results - Urban Map

Screenshot Urban Map (scale 1/20.000)

© Spot Image S.A.,2011. All rights reserved

Urban Mapping Product Results - Statistics

Urban Mapping Product Quality Checks / Initial Validation

EUROSENSE Internal Quality Procedures: Quality control after each production step

Validation Urban Map

− Stratified random control point sample

− Interpretation sample point (blind interpretation & visualization LU code)

− Calculation error matrix

Distribution of a set of 250 points that are used during

validation Error Matrix of classification based on blind interpretation, overall accuracy is 90%

Reference Data

Urban Map

Data 11100 11200 11300 12100 12200 12300 12400 13300 13400 14100 14200 20000 31000 32000 40000 50000

Row

Total

11100 19 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 20

11200 1 56 0 1 0 0 0 0 1 0 0 1 0 0 0 0 60

11300 0 1 8 1 0 0 0 0 0 0 0 0 0 0 0 0 10

12100 0 0 0 9 0 0 0 1 0 0 0 0 0 0 0 0 10

12200 0 2 0 0 6 0 0 0 0 0 0 1 1 0 0 0 10

12300 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

12400 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 10

13300 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 10

13400 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 10

14100 0 0 0 0 0 0 0 0 1 5 0 0 4 0 0 0 10

14200 0 0 0 1 0 0 0 0 0 0 9 0 0 0 0 0 10

20000 0 0 0 0 0 0 0 0 0 0 0 39 1 0 0 0 40

31000 0 1 0 0 0 0 0 0 1 0 0 0 28 0 0 0 30

32000 0 0 0 0 0 0 0 0 0 0 0 0 3 6 0 1 10

40000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

50000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 10

Column Total 20 60 8 13 6 0 10 11 13 5 9 41 37 6 0 11 250

Overall accuracy (225/250)= 90%

Historical Mapping of Terrain Deformation Outputs formats & Guidelines to use

Vector file (shapefiles – UTM WGS84 zone 49S) The database provides:

− Measurement point location

− Ground motion information: mean rate and retrieved

times series (ground motion for each acquisition

date)

− Quality parameters: e.g. SPN model fitting coherence,

standard deviation of the estimations.

Geocoded interpolated raster image (.tiff) − Ground projected image of the ground motion.

− This file provides a fast detection and localization of

any terrain-motions.

Digital map (.png &.pdf) − Map of the measured ground motion at different scales.

− The magnitude of the movement is specified using a color

scale.

− Can be printed at A3 format.

Google Earth files (.kml) − .kml files showing the accumulated motion.

− Easy visualization of the results (in case of no GIS).

Measurement point identifier

Measurement point location in geographic and cartographic

coordinates Quality parameters

Velocity in mm/year


Time series – evolution of the displacement (in mm) Accumulated displacement

over 6.5 years in mm


-40

-30

-20

-10

0

10

20

Dis

pla

cem

en

t in

mm

Acquisition dates of the ENVISAT ASAR images

B973_37_098_B

-40

-30

-20

-10

0

10

20

Dis

pla

cem

en

t in

mm

Acquisition dates of the ENVISAT ASAR images

B973_37_098_B

B967_32_103_E

Historical Mapping of Terrain Deformation Results – ERS data processing

104612 measurement points have been selected (over 1300 km2).

They are mainly located in urban areas and over ground covered by rocks.

The land deformation in the area is displayed with a scale varying from red (>-6mm/yr) to blue (> 6 mm/yr) - The reference point is located in Gamping District (Sleman) in a stable area.

More than 99.8 % of the detected points are stables.

Historical Mapping of Terrain Deformation Results – ERS data processing

Historical Mapping of Terrain Deformation Results – ASAR data processing

Higher number of images and better temporal distribution 636129 points were selected.

They are mainly located in urban areas and over ground covered by rocks.

The land deformation information is displayed with a scale varying from red (>-9mm/yr) to blue (> 9 mm/yr) - Reference point close to the one used for ERS analysis.

More than 96 % of stable points and 4 percent with low magnitude motion.


B2736_6558_100_E

B2623_7853_102_D

B2626_7827_110_E

-60

-50

-40

-30

-20

-10

0

10

November-02 April-04 August-05 January-07 May-08 October-09

Dis

pla

cem

en

t (i

n m

m)

Acquisition dates of the ASAR images

B2736_6558_100_E

B2626_7827_110_E

B2623_7853_102_D

Terrain deformation in Yogyakarta City and Bantul Regency derived from the analysis of ASAR data (2003 - 2009)

Temporal evolution of the point displacement

The gap of information on the points displacement between end 2007 and end 2009 is due to the lack of ASAR data during those two years.

The curves show a clear subsidence with an almost linear trend (light variability is inferior to the precision of measurement)


Historical Mapping of Terrain Deformation Results – ALOS data processing

Historical Mapping of Terrain Deformation Results – ALOS data processing

905101 points were selected.

Regular distribution of measurement points - over the urban areas but also in the surroundings due to the use of L-band data that is less affected by changes in vegetated areas.

The land deformation information is displayed with a scale varying from red (>-15 mm/yr) to blue (> 15 mm/yr) - Reference point in Gamping District.

More than 96 % of stable points, area of landslide detected in Gunung Kidul regency.

Historical Mapping of Terrain Deformation Results – Continuity of the time series

3-year temporal gap between the ERS and ASAR stacks, but overlap of 4 years between ASAR and ALOS analyses.

Comparison of ASAR and ALOS time series:

− Possible in areas where ASAR show high motion rates, considering the 7 mm absolute accuracy of the L-band measurements.

− One area selected as example in Sleman Regency; a good agreement between the time series has been found.

-120

-100

-80

-60

-40

-20

0

9/1/2002 1/14/2004 5/28/2005 10/10/2006 2/22/2008 7/6/2009 11/18/2010 4/1/2012

De

form

ati

on

(m

m)

Dates

ASAR (B2681_2519_100_E) vs ALOS(B785_2010_106_B)

ASAR data

ALOS data

Historical Mapping of Terrain Deformation Quality Checks / Initial Validation

The German Space Agency (DLR) has certified that the PSI processing of Altamira Information was conformed to the Terrafirma Validation Project

standards

Validation

Validated results with external measurements: precise leveling,

GPS, geodesic measurement, extensometers

Quality controls

PSI and InSAR processing steps are precisely controlled according to a quality

control protocol (certified by DLR). The protocol sets down a series of

automated and operator driven quality checks.

Technique developed in-house

Continuous investment in internal developments in PSI. Adaptation of the

technology to the project needs











Agenda

GeoTiff raster file (.tiff)

− Ground projected image of the DSM.

− The GeoTiff raster gives the height values over the overall AOI (1425 km2).

− Can be displayed in GIS and visualized with any image processing software.

− Georeference information allows quick comparison with other spatial data using GIS

Digital map (.png &.pdf)

− Overview map of DSM at scale 1/250.000

− Can be printed at the specified scales.

Precise Digital Elevation Model Output formats & Guidelines to use

SPOT DEM (DSM – Digital Surface Model)

The elevations of the top surfaces of buildings, trees, towers, and other features elevated above the bare earth are included

SPOT DEM: © Spot Image S.A - Background data: © Bing Maps.

SPOT DEM for the Urban Map AOI Full overview SPOT DEM

Precise Digital Elevation Model Output formats & Guidelines to use


− Different thematic maps have been produced (hazard, vulnerability and risk indices)

− Can be printed at different scales (up to A0)

Vector file (shapefiles in UTM WGS84 49S) − Files giving information on:

o Geography of the AOI (districts, borders, roads, rivers…)

o Hazards and Multi-hazard index

o Land use

o Vulnerability and risk assessment

− Attribute table with different fields

− Visualization in GIS

Multi-Hazard Vulnerability Mapping Output formats & Guidelines to use

Geocoded raster file (.img)

− Ground projected image of the DEM.

− The gives the height values over the overall AOI.

− Can be displayed in GIS and visualized with any image processing software (georeference information)

Tropical Storm

Merapi Debris Earthquake Tsunami

Landslide Flood

Multi-Hazard Vulnerability Mapping Results – Hazard Maps

Multi-Hazard Vulnerability Mapping Results – Multi-Hazard Indices

Multi-Hazard Index Sub-District Multi-Hazard Index

The multi-hazard information is transferred to Sub-District level (elementary cell of the mapping.)

Multi-Hazard Vulnerability Mapping Results – Vulnerability Index

Risk = Hazard x Vulnerability

Multi-Hazard Vulnerability Mapping Results –Risk Index

Vector files (Shapefile – Projection UTM WGS84 49S)

− Attribute table with different fields (depending on the corresponding maps)

− Integration of GIS database (layer files) and easy update

− Statistical data for further analysis and indicator extraction


Overview maps and maps sheets for index

−Maximum water depth

−Impact on land use classes Easy printing and visualization by different delivery formats

Raster geodatabase (.gdb)

− 96 water depth rasters – 24h each 15 min

− 1 standard legend layer for complete raster geodatabase

Animation movie (.wmv)

− Provides crucial information about the propagation and lahar velocity

− Can be played on any standard pc

Flood Hazard Mapping Output formats & Guidelines to use

Flood Hazard map (max water depth raster) for the Merapi lahar event of November 2010, Yogyakarta (Indonesia), 1/150.000

Flood Hazard Mapping Results – Flood Hazard Map database

The flood hazard map (max water depth raster) for the Merapi lahar event of November 2010, Yogyakarta (Indonesia), 1/150.000

Flood Hazard Map database

specific water depth for all pixels

for each 15 min during 24 hours

Maximum water depth raster

max value of each cell in the 96 rasters is retained

All rasters use the same legend (water depth in meter)

Flood Hazard Mapping Results – Flood Hazard Map database

Animation movie of the Merapi lahar event of November 2010, Yogyakarta (Indonesia) showing the flood propagation

Flood Hazard Mapping Results – Flood Hazard Animation

lahar_merapi_2010_simulation_HD.wmv

Flood Hazard Mapping Results – Flood Hazard Impact

Overview of the flood hazard impact on land use for the Merapi lahar event of November 2010, Yogyakarta (Indonesia), 1/110.000

Flood Hazard Mapping Results – Flood Hazard Impact

Flood Hazard Impact on land use classes

affected built-up area

using a gradient of colors representing the water depth

Overview of the flood hazard impact on land use for the Merapi lahar

event of November 2010, Yogyakarta (Indonesia), 1/110.000

Flood Hazard Mapping Quality checks, Initial Validation

Validation of the simulation process

FloodArea software validated by scientific & commercial references and qualification procedures in EC/ESA projects

Simulation is validated via repetitive cycle of calibration, adaptations in input layers and parameterization

Simulation result can only be as good as the input data (e.g. resolution, geolocation accuracy, vertical accuracy…)

Validation of the Flood Hazard Maps database

Risk zones

Flood Extent

By sources:

Local information in reports and articles of newspapers/press

Reference inundation maps

No scientific reference data available

Flooded regencies of Sleman, Bantul and Yogyakarta City

Risk zones

Flood Extent

Comparison between simulated extent and past flood map

Flood Hazard Mapping Quality checks, Initial Validation

The threat zone of cold lava flood is situated within a buffer of 300 to 500 m distance

from the rivers for the region of Merapi cold lava flood

The hazard simulation is based on available EO and ancillary data, without the use of in-situ data, neither for calibration nor for validation purposes

Good agreement between the several sources and the delivered products

National Disaster Management Agency of Indonesia

Representation of threat zones of 300m (left) and 500m (right) overlaid to the flood hazard map

Agenda











Up-to-date/Rapid update

Harmonized approach

Hierarchical approach

High level of detail

Global uniformity of EO data creates comparable products

Standard legend can be applied globally

Suitable for integration in urban and risk analysis (statistics)

Legend follows an hierarchical approach, adapted to MHCRI legend

Allows an interpretation up to the highest level

Based on VHR EO data (2,5m or better) – MMU is 0,25 ha

High urban thematic detail focused with more than 25 classes

However some limitations…

High level interpretation requires reliable non-EO information

Demonstration products Operational Products

Advantages / Constraints & Recommendations Urban Map of infrastructures and buildings

Based on recent EO data (Feb 2011) – large coverage

Vector approach allows an easy update - Automatic update of building densities and building heights

Advantages / Constraints & Recommendations Urban Map of infrastructures and buildings

Include a field campaign before production to collect ancillary data/have a local contact thematic detail and accuracy of urban map will increase

Align AOI’s with administrative boundaries to facilitate integration with other data (e.g. risk analysis)

Regular new acquisition of EO data to keep the Urban Map up-to-date and detect changes.

Acquire new stereo pair EO to produce Building height map

High quality measurement & Cost efficiency

Retrospective analysis

Up to date information

Large coverage

Extensive number of measurement points (in space) compared to other methods (close to 1M with ALOS).

Cost efficient, especially for large surfaces as no in-situ activities required

Sub-mm yearly rates, mm vertical accuracy, 2 m horizontal accuracy

Archive data available for historical ground motion analysis

Terrain deformation assessed over 14 years

Ground motion monitoring based on the latest ALOS archive (up to beginning 2011).

Large area monitoring compared to in-situ methods

Terrain deformation assessed over the ERS, ASAR and ALOS frames

Advantages / Constraints & Recommendations Historical Mapping of Terrain Deformation

Slight motion in Yogyakarta City cannot be assessed with

ALOS data

However some limitations...

Advantages / Constraints & Recommendations Historical Mapping of Terrain Deformation

Further monitoring of the detected deformations patterns

Future monitoring using very high spatial resolution satellites (RADARSAT-2, TerraSAR-X, COSMO-SkyMed, etc.) must be considered to locally control the deformation areas:

− Higher revisit rate allows to rapidly build suitable data archive

− Better temporal distribution of measurements allows to better assess changes of trend of the subsidence.

− Short revisit time also allow fast motion to be monitored.

− Spatial Resolution achieved with VHR imagery of 3 m (40 m in the case of the ERS and ENVISAT missions) higher number of measurement points, mainly in urban areas and evaluate how single infrastructure is affected.

− Better detection accuracy (lower noise level) could be achieved in Yogyakarta City.

This continuous monitoring, taking into account interpretation with ground truth and geological information, will allow to detect locally new

deformation phenomena.

CSK archive

Archive_Yogya_CSK.png

No DTM could be generated due to the lack of a suitable stereo data. Recommendations for service improvement would be:

− Acquire new EO stereo pairs

− Work with high resolution stereo couple data (e.g. 1m (Ikonos) or higher resolution)

− More than 1 stereo couple (different angles)

− Increased quality of images (radiometric, cloud free, etc.)

− Better ground control (planimetric and altimetric points)

Advantages / Constraints & Recommendations Precise Digital Elevation Model

Advantages / Constraints & Recommendations Multi-Hazard Vulnerability Mapping

First steps of vulnerability mapping and risk analysis in the Province of Yogyakarta.

Foreseen improvements concern:

Hazard analysis:

− Up to date information (PIP2B information dates of 2004) with feedback of WB, ADB, users….

− Complete the flood risk analysis (validation of Add Des Info 3)

− Focus on Yogyakarta City

Vulnerability assessment methodology

− How to integrate the terrain deformation results in the vulnerability assessment?

− Complete the vulnerability Assessment procedure need for data

Risk Analysis

− Smaller spatial scale (sub-district scale, 500 m cell level in MHRCI)

− Consider Yogyakarta City transfer to MHRCI (need for data + WB feedback)

Retrospective Analysis

Large coverage application

Not just a map package

Insight into the evolution, extent and consequences of the lahar flood event of November 2010

Better assessment by EO-data deducted products of areas and population/goods in danger

This Flood simulation allows large scale assessment not only focusing on Yogyakarta solely

Shows natural propagation and velocity of the cold lava flood at a generic level which allows large area coverage

Maximum water depth during 24h time span

Support in all risk management phases to take efficient measures in prevention phase and during crisis

Integrates worldwide spatial with non-spatial information

However some limitations…

Required input data and information is high demanding

Flood simulations remain an estimation to assess “the reference”

Quasi 2-D hydraulic model <-> Detailed 3D-model

Demonstration products Operational Products

Advantages / Constraints & Recommendations Flood Hazard Maps and Flood Hazard Impact

Advantages / Constraints & Recommendations Flood Hazard Maps and Flood Hazard Impact

Integration of the map package and GIS data in local flood event database

The hazard simulation can be improved with the use of reference data

Use of the same model for simulation of other scenario’s (more extreme rainfall, smaller eruption, changes of land use,…) which can predict new events in the future

Combination with vulnerability and population data to assess risk and damage to population and goods damage functions and assets maps

Adaptation and customization for correspondence or integration into World Bank requirements

Next step is to assess your feedback and the one of the Users.

Assess to what extent the services responded to the specified user requirements and elaborate any potential improvements

necessary to resolve identified short-comings

Questionnaire with 25 questions to assess feedback in terms of usefulness, availability, reliability and affordability AI_eoworld_HCMC_YOGYA_User_Feedback_v1.0.pdf.

Organization of a follow-on teleconference (in 2-3 weeks) in order to get the most valuable feedback and define together the necessary improvements.

User Feedback Assessment Questionnaire

AI_eoworld_HCMC_YOGYA_User_Feedback_v1.0.pdf

Date : 21 February 2012

Thank you

Questions & Discussions

Documents

EO Information Services in support of Multi-Hazard …siteresources.worldbank.org/EXTEOFD/Resources/84267… · · 2012-05-10Multi-Hazard Vulnerability Assessment in Yogyakarta