EO Information Services in support of Satellite Tools for Building Flood Defence Systems in Guyana

Transcription

1 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 Date : 21 February 2012

2 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

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

4 EO information Products Methodologies Generation of Service 1 outputs VHR SAR based interferometric terrain deformation mapping 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 Spatial resolution Absolute location accuracy Relative X, Y accuracy Velocity measurement accuracy Absolute accuracy (time series) TS-X frame TerraSAR-X 3 m Better than 1-2 m Metric in both E-W and N-S direction 3 mm/year 5 mm

5 EO information Products Methodologies Generation of Service 1 outputs Data extraction: The SAR images and the acquisition parameters are extracted from the SAR data products The SPN (Stable Point Network) processing 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

6 EO information Products Methodologies Generation of Service 2 outputs 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. Source data Format 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 GIS compatible vector/ raster layer Scale 1: MMU Area produced 0.25 (urban area) 0.5 ha (rural area) 402 km² Reference date Accuracy Thematic: > 80 % Geometric: < 1m Includes material GeoEye, alle rights reserved

7 EO information Products Methodologies Generation of Service 2 outputs Preprocessing EO imagery Ancillary data -OSM -Wikimapia -Google Earth -BingMaps Preprocessing Points & lines Prelim. urban map Sealing layer Manual delineation & Interpretation GIS processing Urban map Calculation urban densities Urban parameters GIS calculations Visual interpretation Ancillary data (Pictures) Height data (Add des inf 1)

8 EO information Products Methodologies Generation of Add Des Inf 1 outputs High Resolution DEM 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. Coverage 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 Spatial resolution Vertical accuracy Global topography Precise height information 2130 Km Km 2 9 m 9 m 7 m 1-2 m

9 EO information Products Methodologies Generation of Add Des Inf 2 outputs 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) Breaches in the dam => excess water discharged to the canals leading to the Mahaica River Picture taken during the flood event (17/01/2005) with some recognizable spots marked. Dominic Mendes ( Reference layer water bodies Past Flood Extent (max) layer 2 ENVISAT ASAR Feb 8 th & 13 th, 2005 Normal Demerara River extent is derived by a semi-automatic classification from post-disaster ENVISAT ASAR (Dec 1 st 2005) Object oriented semi-automatic classification based on spectral information Interpretation and editing to 6 classes with Prob A & Prob B Additional infrastructure layers Roads, railways, sluices, dams AOI of the Flood risk assessment

10 EO information Products Methodologies Generation of Add Des Inf 2 outputs 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 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

11 EO information Products Methodologies Generation of Add Des Inf 2 outputs Flood Risk Assessment Map: Gives information about the impact caused by a flood in terms of affected people and economical damage 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 Damage functions

12 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

13 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. Google Earth files (.kml).kml files showing the accumulated motion. Easy visualization of the results (no need of GIS). 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.

14 VHR Terrain Deformation Mapping Outputs formats & Guidelines to use Measurement point identifier Measurement point location in geographic and cartographic coordinates Velocity in mm/year Quality parameters Time series

15 Displacement in mm VHR Terrain Deformation Mapping Outputs formats & Guidelines to use Time series evolution of the displacement (in mm) Accumulated displacement over 8 months in mm B9894_4190_098_C B9933_4010_102_D B9933_4010_102_D Acquisition dates of the TerraSAR-X images

16 VHR Terrain Deformation Mapping Presentation of the results

17 VHR Terrain Deformation Mapping Presentation of the results 1.2 M 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

18 VHR Terrain Deformation Mapping Presentation of the results

19 Displacement in mm VHR Terrain Deformation Mapping Presentation of the results B1066_3897_097_C B0853_3910_096_C B0827_3912_095_D B0683_3923_098_C B0643_3926_098_C Ogle Koker 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/ B1066_3897_097_C B0853_3910_096_C B0827_3912_095_D B0683_3923_098_C B0643_3926_098_C Dates d'acquisition des données TerraSAR-X

20 VHR Terrain Deformation Mapping Quality Checks / Initial Validation Technique developed in-house Continuous investment in internal developments in PSI. Adaptation of the technology to the project needs 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. 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

21 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/ and map sheets at scale 1/ Can be visualized with any image viewing software and printed at A3 format

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

23 Urban Mapping of infrastructures and buildings Presentation of the results Screenshot Urban Map, Georgetown (Guyana), 1/ Includes material (c) GeoEye, alle rights reserved

24 Urban Mapping of infrastructures and buildings Presentation of the results Screenshot Urban Map, Georgetown (Guyana), 1/ Includes material (c) GeoEye, alle rights reserved

25 Urban Mapping of infrastructures and buildings Presentation of the results Construction Parameters Building Density Building Material Building Distance Building Footprint Building Height Building Floor Area Building Distance Legend to drainage systems 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 Building Distance to drainage systems Legend Distance_to_Drainag <VALUE> , , , , , , , , , , , , , , , ,1-800,0 400,1-800 vector 800,1-1600,0 raster 800,

26 Urban Mapping of infrastructures and buildings Presentation of the results Statistics Artificial surfaces Urban fabric Construction sites & Land without current use 1 Industrial, commercial, pbulic, military and private services Water suply and protection infrastructure Transportation netw ork Mine, dump and construction sites 1 Land w ithout current use Construction sites Urban green Sports and leisure facilities 0% 20% 40% 60% 80% 100% Artificial non-agricultural vegetated area 0% 20% 40% 60% 80% 100% Urban fabric Transportation network 1 Very dense urban fabric Dense urban fabric Medium dense urban fabric Low dense urban fabric 1 Fast transit roads Other roads Port areas Airport 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Building Material Building Distance Building Footprint Building Height

27 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 Urban Map Data Reference Data Row Total Column Total Overall accuracy (112/115)=97% Parameter Accurate Indicative Urban map Building density Building material Building distance Building footprint Building height Building floor area X X X X X X X Error Matrix of classification (level 2) based on blind interpretation (Code 1), overall accuracy is 97% Distance to drainage systems X

28 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

29 High Resolution DEM Output formats & Guidelines to use 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 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. Digital map (.png &.pdf) Digital map of the measured height. Can be printed at A3 format.

30 High Resolution DEM Presentation of the results

31 High Resolution DEM Presentation of the results

32 Number of PS High Resolution DEM Presentation of the results Height information in Georgetown PS Total Height (SRTM+error_DEM) Histogram of the PS height values The PS total height histogram is not centered at zero, since topographic information is mainly recovered from urban structures (buildings ). 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) Maximal height Minimal height Mean height Height Stddev 45.6 m -4.3 m 9.48 m 6.02 m This information has been used for Service 2. The service validation is based on the one of Services 1 and 2.

33 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 Flood Risk Analysis Output formats & Guidelines to use Digital map (.pdf &.png) Atlases of maps in pdf and png (hardcopy print) Asset Maps Atlas = 18 sheets for NUTS regions 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

34 Flood Risk Analysis Results Past Flood Map

35 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

36 Flood Risk Analysis Results Asset Maps Population Density Total Assets Value

37 Number of affected persons Flood Risk Analysis Results Flood Risk Assessment Total economical damage 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] Georgetown councils Total affected population in relation with the Total Population for each council. [X: council name; Y: # of people]

38 Flood Risk Analysis Quality checks, Initial Validation Past Flood Map The mapped inundated areas are significantly concordant with the reference data 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 Rapid Response Inundation Map 2005 (Guyana) Dartmouth Flood Observatory 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 inh inh 97% Region inh inh 84% Region inh inh 102% Region inh inh 48% Housing ,57 32% Household , ,94 32% Vehicles , ,00 299% Livestock , ,04 70% Roads , ,00 75% Agriculture , ,64 246% Industry , ,88 733% Service & trade , ,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

39 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

40 Advantages / Constraints & Recommendations Terrain Deformation Mapping Large coverage High quality measurement & Cost efficiency Large area monitoring compared to in-situ methods Terrain deformation assessed over a TerraSAR-X frame Extensive number of measurement points (in space) compared to other methods (3200 points/km 2 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 Retrospective analysis Archive data available for historical ground motion analysis Terrain deformation assessed over 8 months, new archive available Up to date information Ground motion monitoring based on the up to date TerraSAR-X archive (end ). Change of motion trend could be rapidly assessed.

41 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

42 Advantages / Constraints & Recommendations Urban Map of infrastructures and buildings High level of detail Up-to-date/Rapid update Based on VHR EO data (2,5m or better) MMU is 0,25 ha High urban thematic detail focused with more than 25 classes Based on recent EO data ( ) large coverage Vector approach allows an easy update - Automatic update of building densities and building heights Harmonized approach Hierarchical approach However some limitations 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 Construction parameters need support from reliable ancillary data High level interpretation requires reliable non-eo information Demonstration products Operational Products

43 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

44 Advantages / Constraints & Recommendations Flood Risk Analysis Maps Not just a map package Support in all risk management phases Integrates worldwide spatial with non-spatial information Retrospective analysis Standardized & up to date However some limitations 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 Required input data and information is high demanding Flood risk remains an estimation to assess the reference Demonstration products Operational Products

45 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

46 User Feedback Assessment Questionnaire 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.

47 Thank you Questions & Discussions Date : 21 February 2012