eo information services in support of satellite tools for building

Date : 21 February 2012

EO Information Services in support of

Satellite Tools for Building Flood Defence Systems in Guyana

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 – VHR Terrain deformation Mapping

– Urban Mapping of infrastructure & buildings

The EO Information Additional Services – High Resolution Digital Elevation Model

– Flood Risk Analysis

Conclusion & User Feedback – Advantages / Constraints & Recommendations

– User Feedback Assessment

Delivered EO information Products/Services

Objectives of the project:

Estimation of possible subsidence phenomena in the coastal lowland and to study the flood defense system

EO satellite based solution composed of 2 main services and 2 additional ones*.

Service 1: VHR SAR based interferometric terrain deformation mapping

Service 2: Urban mapping of infrastructure & buildings

Additional Service 1: High Resolution DEM

Additional Service 2: Flood risk Analysis: Past Flood Map + Asset Map + Flood Risk Assessment

*The Additional Desirable Information 3 (Accurate estimation of the effective rate of sea level rise) was not performed due to the lack of input data.

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

VHR SAR based interferometric terrain deformation mapping

EO information Products Methodologies Generation of Service 1 outputs

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

InSAR study based on VHR TerraSAR-X satellite data - optimal to achieve high density measurements in specific constructed areas

− 22 SAR images acquired each 22-day period.

− Monitoring period from 08/2010 to 04/2011

TS-X frame

TerraSAR-X

Spatial resolution 3 m

Absolute location accuracy

Better than 1-2 m

Relative X, Y accuracy Metric in both E-W and N-S direction

Velocity measurement accuracy

3 mm/year

Absolute accuracy (time series)

5 mm

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


Source data

GeoEye-1 & Ikonos satellite imagery

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

Height info from Add Des Info 1

Remark: Urban Map based on Bing Maps (VHR) where cloud coverage is important

Format GIS compatible vector/ raster layer

Scale 1:10.000

MMU 0.25 (urban area) – 0.5 ha (rural area)

Area produced 402 km²

Reference date 2009 - 2011

Accuracy Thematic: > 80 % Geometric: < 1m

Urban mapping of infrastructure & buildings

Urban map: representation of the location of urban infrastructures

A part of the Coastal Lowland of Guyana, along the East Coast Demerara and includes the city of Georgetown is mapped.

Includes material © GeoEye, alle rights reserved


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

Sealing layer

Prelim. urban map

Urban map

Urban parameters

Calculation urban densities

• GIS calculations • Visual interpretation • Ancillary data (Pictures) • Height data (Add des inf 1)

Preprocessing Preprocessing

• Manual delineation & Interpretation

• GIS processing

Points & lines

EO information Products Methodologies Generation of Add Des Inf 1 outputs

High-resolution topographic map of Georgetown, based on the use of TerraSAR-X data.

Generation of the DEM based on the combination of low spatial resolution information (SRTM topographic model) with high resolution one (PSI processing residual height information).

High precision height values only obtained in urban areas.

Height precision on PS points is about 1-2 meters, while the rest of areas present an error of about 7 meters in height.

SRTM map has been interpolated at a higher spatial resolution (9 m)

Summing of precise height values derived from the Service 1

processing resampled to 9 m

Global topography

Precise height

information Coverage

2130 Km2 390 Km2

Spatial resolution 9 m 9 m

Vertical accuracy 7 m 1-2 m

High Resolution DEM


Past Flood Extent (max) layer

− 2 ENVISAT ASAR Feb 8th & 13th, 2005

− Object oriented semi-automatic classification based on spectral information

− Interpretation and editing to 6 classes with Prob A & Prob B

AOI of the Flood risk assessment

Reference layer water bodies

− Normal Demerara River extent is derived by a semi-automatic classification from post-disaster ENVISAT ASAR (Dec 1st 2005)

Additional infrastructure layers

− Roads, railways, sluices, dams

Past Flood Map: Localizes the (maximum) flood extent observed at the time of image acquisition from an event in the past

Guyana Coastal Belt

− Lying 1-4 meters below mean sea level

− Subject to Atlantic swells, heavy seasonal rainfall and high humidity

− Highest populated area in Guyana

East Demerara Water Conservancy Dam

− Well-designed system of drainage and irrigation canals, conservancy dams and seawalls

Flood Event January-February 2005

− Caused by heavy rainfall (14-22/01)

− One of the worst floods in Guyana (return period >100 years)

Picture taken during the flood event (17/01/2005) with some recognizable

spots marked. © Dominic Mendes (www.djmgy.com)

Breaches in the dam => excess water discharged to the canals leading to the Mahaica River


Input data:

Generic land use and land cover data

− Urban Map (Service 1) & Globcover Land Cover

Socio-economic data and statistics

− Guyana Bureau of Statistics

− World Bank Statistics

− Food and Agriculture Organization (FAO) Statistics

Additional data on infrastructures, local info

− BingMaps layer, Google Earth, OpenStreetMap

Asset Maps: Population distribution and economical assets distribution for different damage classes

based on NUTS administrative borders

Conversion Globcover to Urban Map classes

Disaggregating top down socio-econ values by generic geographical information


Past flood map − Flood extent and water level info (depth)

Asset Maps

Damage Factors

− Calculated by damage functions based on water depth for a specific damage class,

− Damage caused by a flood is calculated by a modeled approach per polygon (by multiplying a damage factor with the values of the Assets map )

− Classification in relative risk classes from very high, over medium, to very low risk

Damage to telecommunications building © UNDP report “Guyana socio-economic assessment of the damages and losses

caused by the January-February 2005 flooding”

Flood Risk Assessment Map: Gives information about the impact caused by a flood in terms of affected people and economical damage

Damage functions

Agenda










VHR Terrain Deformation Mapping Outputs formats & Guidelines to use

Vector file (.shp – UTM PSAD 56 21N) 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 (no need of GIS).

Measurement point identifier

Measurement point location in geographic and cartographic

coordinates Quality parameters Time series

Velocity in mm/year


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

over 8 months in mm


-15

-10

-5

0

5

10

15

Dis

pla

cem

en

t in

mm

Acquisition dates of the TerraSAR-X images

B9933_4010_102_D

-15

-10

-5

0

5

10

15

Dis

pla

cem

en

t in

mm

Acquisition dates of the TerraSAR-X images

B9894_4190_098_C

B9933_4010_102_D

VHR Terrain Deformation Mapping Presentation of the results

1.2M of measurement points have been selected.

They are mainly located in urban areas where infrastructures are present.

The accumulated displacement in the AOI is represented by a colour scale varying from red (subsidence >-18mm) to blue (uplift > 18mm).

The reference point (motion = 0) is a point of good quality selected automatically


B1066_3897_097_C

B0853_3910_096_C B0827_3912_095_D

B0643_3926_098_C

B0683_3923_098_C

Ogle Koker

-25

-20

-15

-10

-5

0

5

Dis

pla

ce

me

nt i

n m

m

Dates d'acquisition des données TerraSAR-X

B1066_3897_097_C

B0853_3910_096_C

B0827_3912_095_D

B0683_3923_098_C

B0643_3926_098_C

A high number of measurement points have been detected along the seawall,

Instability of the seawall structure can be detected close to the Ogle Kocker, which is used to control the flow of water in the drainage canals (trenches) in the city.

Higher measured displacements reach -20 mm from 08/2010 to 04/2011


VHR Terrain Deformation Mapping 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

Urban Mapping of infrastructures and buildings Outputs formats & Guidelines to use

Vector files (.shp – UTM PSAD 56 21N) − Can be used in a GIS environment (corresponding layer files). − Attribute table with different fields which give more information about each polygon

(i.e. building material, footprint, building density, area etc.

Geocoded Raster file − It represents the distance to drainage systems

Digital map (.pdf & .png) − Overview maps of urban map and construction

parameters at scale 1/120.000 and map sheets at scale 1/10.000.

− Can be visualized with any image viewing software and printed at A3 format

Urban Mapping of infrastructures and buildings Outputs formats & Guidelines to use

Includes material (c) GeoEye, alle rights reserved

Screenshot Urban Map, Georgetown (Guyana), 1/10.000

Urban Mapping of infrastructures and buildings Presentation of the results

Building Density Building Material Building Distance Building Footprint

Building Height Building Floor Area

Building Distance to drainage systems

Building Distance to drainage systems

raster vector

Legend

Distance_to_Drainage_Systems

<VALUE>

0

0 - 10

10,1 - 20

20,1 - 30

30,1 - 40

40,1 - 50

50,1 - 60

60,1 - 70

70,1 - 80

80,1 - 90

90,1 - 100

100,1 - 150

150,1 - 200

200,1 - 250

250,1 - 300

300,1 - 350

350,1 - 400

400,1 - 800

800,1 - 1.600

Legend

Service_2

Min_Dist_D

0

0,1 - 10,0

10,1 - 20,0

20,1 - 20,0

20,1 - 30,0

30,1 - 40,0

40,0 - 50,0

50,1 - 60,0

60,1 - 70,0

70,1 - 80,0

80,1 - 90,0

90,1 - 100,0

100,1 - 150,0

150,1 - 200,0

200,1 - 250,0

250,1 - 300,0

300,1 - 350,0

350,1 - 400,0

400,1 - 800,0

800,1 - 1600,0


Construction Parameters


0% 20% 40% 60% 80% 100%

1

Artificial surfaces Urban fabric

Industrial, commercial, pbulic, military and

private services

Water suply and protection infrastructure

Transportation netw ork

Mine, dump and construction sites

Artif icial non-agricultural vegetated area

0% 20% 40% 60% 80% 100%

1

Urban fabric

Very dense urban fabric

Dense urban fabric

Medium dense urban fabric

Low dense urban fabric

0% 20% 40% 60% 80% 100%

1

Transportation network

Fast transit roads

Other roads

Port areas

Airport

0% 20% 40% 60% 80% 100%

1

Construction sites & Land without current use

Land w ithout current use

Construction sites

Urban green

Sports and leisure facilities

Building Material Building Distance Building Footprint Building Height

Statistics

Urban Mapping of infrastructures and buildings 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

Validation construction parameters per street block

Reference Data

Urban Map

Data 11000 12000 13000 14000 20000 31000 32000 40000 50000 Row Total

11000 40 0 0 0 0 0 0 0 0 40

12000 0 20 0 0 0 0 0 0 0 20

13000 0 0 5 0 0 0 0 0 0 5

14000 0 0 0 5 0 0 0 0 0 5

20000 0 0 0 0 20 0 0 0 0 20

31000 0 0 0 0 0 6 0 0 0 6

32000 0 0 0 1 0 1 2 1 0 5

40000 0 0 0 0 0 0 0 9 0 9

50000 0 0 0 0 0 0 0 0 5 5

Column

Total 40 20 5 6 20 7 2 10 5 115

Overall accuracy (112/115)=97%

Error Matrix of classification (level 2) based on blind interpretation (Code 1), overall accuracy is 97%

Parameter Accurate Indicative

Urban map X

Building density

X

Building material

X

Building distance

X

Building footprint

X

Building height

X

Building floor area

X

Distance to drainage systems

X

Agenda










GeoTiff raster file (.tiff)

− Ground projected image of the ground motion.

− The GeoTiff raster gives the height values over the overall AOI (2m vertical accuracy in Georgetown and along the Demerara River, 7 m elsewhere).

− Mask of the precise height information.

Binary raster (.bin)

− The binary raster file consists of two files, the IEEE floating-point file and a supporting ASCII header file.

− It can be used in various applications.

Vector file (.shp – UTM PSAD56 21N) The database provides:

− Measurement point location: UTM Easting/Northing

− Height information: PSI retrived height, SRTM height and total height

Digital map (.png &.pdf)

− Digital map of the measured height.

− Can be printed at A3 format.

High Resolution DEM Output formats & Guidelines to use

High Resolution DEM Presentation of the results

In Georgetown, due to the high density of PS, single building height can be retrieved (2 m vertical accuracy ).

The mean height is of about 9.48 m: presence of many small houses (between 4 and 8 m height) and of some tall buildings (between 20 and 25m height)

This information has been used for Service 2.

The service validation is based on the one of Services 1 and 2.

0

2000

4000

6000

8000

10000

12000

14000

16000

-15 -10 -5 0 5 10 15 20 25 30 35 40 45

Nu

mb

er

of

PS

PS Total Height (SRTM+error_DEM)

Maximal height 45.6 m

Minimal height -4.3 m

Mean height 9.48 m

Height Stddev 6.02 m

Histogram of the PS height values

Height information in Georgetown

High Resolution DEM Presentation of the results

The PS total height histogram is not centered at zero, since topographic information is mainly recovered from urban structures (buildings…).

Vector files (.shp – UTM PSAD 56 21N)

− Created for Past Flood Map, Asset Maps and Flood Risk Assessment Maps.

− Attribute table with different fields (classes, population, asset values depending on the corresponding maps)

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

− GIS visualization capabilities to make other representations

− Statistical data for further analysis and indicator extraction

Raster radar file − ENVISAT ASAR imagery on

which the flood extent layer is based

Digital map (.pdf & .png) Atlases of maps in pdf and png (hardcopy print)

− Asset Maps Atlas = 18 sheets for NUTS regions 3-4-5

− Past Flood Map= 7 sheets for the AOI of the Archive Envisat

− Flood Risk Maps: 7 sheets corresp. to the Past Flood Map

Easy printing and visualization by different delivery formats

Flood Risk Analysis Output formats & Guidelines to use

Flood Risk Analysis Results – Past Flood Map

Flood Risk Analysis Results – Past Flood Map

6 main flood classes (incl. non-flooded), with an indication of Probability

− Prob. A - very certain and purely based on spectral information

− Prob. B - indicated as flooded based on a more profound interpretation with the support of ancillary data

Additional layers:

− East Demerara Water Conservancy Dam

− Series of sluice gates, or kokers

− Main roads and Railways

Flood Risk Analysis Results – Asset Maps

Total Assets Value Population Density

Georgetown councils

Num

ber o

f affe

cted p

erso

ns

Total affected population in relation with the Total Population for each council.

[X: council name; Y: # of people]

Affected population

Total Economical Damage of the Affected Area by the Flood Event of February 2005 for each Council.

[X: council name; Y: # of people]

Total economical damage

Flood Risk Analysis Results – Flood Risk Assessment

Flood Risk Analysis Quality checks, Initial Validation

Past Flood Map

Rapid Response Inundation Map –2005 (Guyana) © Dartmouth Flood Observatory

Photographs & pictures

of the flood at acquisition

time of the EO-data

Local information

in reports and articles

of newspapers/press

(UNDP report)

Plausibility check

Reference inundation maps

Flood Risk Assessment

Damage functions (scientific references)

Plausibility check (the real losses of the event

less than ±30% of the maximum calculated loss)

Comparison of the Flood Reference Picture Maps with the Flood Risk Assessment maps

worst hit areas contain the highest damage and

affected population

Damage class Flood Risk Map UNDP report Accuracy

Aff. population 267 026 inh 274 774 inh 97%

Region 3 35 015 inh 41 787 inh 84%

Region 4 227 037 inh 222 522 inh 102%

Region 5 4 974 inh 10 464 inh 48%

Housing 60 972 726 49 190 107 373,57 32%

Household 36 583 635,89 114 551 878,94 32%

Vehicles 3 014 529,62 1 009 080,00 299%

Livestock 2 316 073,47 3 042 507,04 70%

Roads 13 131 555,70 17 600 000,00 75%

Agriculture 141 531 737,16 57 648 265,64 246%

Industry 39 504 753,64 5 390 056,88 733%

Service & trade 74 593 066,18 81 152 736,30 75%

Total damage values (in terms of inhabitants and USD) from the Flood Risk Assessment Maps and from the UNDP report on the flood event of Feb 2005

The mapped inundated areas are significantly concordant with the reference data

Agenda










High quality measurement & Cost efficiency

Retrospective analysis

Up to date information

Large coverage

Extensive number of measurement points (in space) compared to other methods (3200 points/km2 in urban zones)

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

Sub-millimetre yearly rates

Millimetric vertical accuracy, 2 m horizontal accuracy

Archive data available for historical ground motion analysis

Terrain deformation assessed over 8 months, new archive available

Ground motion monitoring based on the up to date TerraSAR-X archive (end 2010 - 2011).

Change of motion trend could be rapidly assessed.

Large area monitoring compared to in-situ methods

Terrain deformation assessed over a TerraSAR-X frame

Advantages / Constraints & Recommendations Terrain Deformation Mapping

Validation of the terrain deformation measurements

− Location of the reference measurement point

− Motion detected on the seawall with available GPS measurement

Increase of the measurement quality

− Limited number of images has been used (only archive available at the start of the project).

− The data provider was asked to continue the data acquisition in order to allow a consistent data archive to be built.

o Important for monitoring continuity and update of the terrain deformation information

o Avoid gap in the data acquisitions for optimal processing

− The extension of the monitoring period to a year increases the possibility to detect and monitor more motion patterns.

o More accurate annual motion rate can be derived

o Increasing of the quality of the terrain deformation measurement

Advantages / Constraints & Recommendations Terrain Deformation Mapping

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

Allows an interpretation up to the highest level and analysis at different levels

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…

Construction parameters need support from reliable ancillary data

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 (2009 – 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, e.g.:

− Improve distinction between thematic classes (e.g.: between commercial and industrial areas)

− Improvement reliability of the construction parameters

− Increase the thematic accuracy of construction parameters (e.g. for the assessment of building material)

− Production of a modified sealing map (used to calculated building densities). At this moment, quality requirements for the sealing map are set at 80% accuracy.

− Building height map could be improved by using a more detailed digital surface model with a high density coverage and vertical accuracy.

Adapt legend to specific needs of the WB

Retrospective analysis

Standardized & up to date

Not just a map package

Insight into the evolution, extent and consequences of the flood event of February 2005 as part of the “Flood memory”

Mapping of the location of vulnerabilities and areas that suffered the highest losses (population, economic,…)

Geo-database based on Administrative borders (NUTS) and standard statistics

Calculation of potential losses in terms of population and economical damages can be performed for other (future) events

Easy update with actual spatial and socio-economic statistics

Support in all risk management phases

Integrates worldwide spatial with non-spatial information

However some limitations…

Required input data and information is high demanding

Flood risk remains an estimation to assess “the

reference”

Demonstration products Operational Products

Advantages / Constraints & Recommendations Flood Risk Analysis Maps

Advantages / Constraints & Recommendations Flood Risk Analysis Maps

Past Flood Map

Integrate map package and GIS data in local flood event database

Evaluate with local water management authority the flood risk analysis in order to improve prevention measures

Asset Maps

Update when

− new geodata (Globcover & more actual urban maps) become available

− new socio-economic statistics become available

Multi-risk same database can be used for several hazards and emergency situations

Exchange with WB on standardization for economical and population values

Flood Risk Assessment Map

Demonstration product to be more calibrated by validation

Further adaptation and customization for correspondence or integration according to WorldBank requirements

Operational up-to-date geo-database for automatic updated assets and flood risk map creation for potential floods of different return periods and future events

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_GUYANA_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_GUYANA_User_Feedback_v1.0.pdf

Date : 21 February 2012

Thank you

Questions & Discussions

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