1. GIS systems in Haiti Shelter focus Shelter Meeting 10a, Geneva 27-28 May 2010 Einar Bjorgo

2. 2 Unpresedented number of mapping efforts and Geographic Information System (GIS) initiatives Actors include  CNIGS (Haiti National Mapping Agency)  OCHA  IOM  WFP  iMMAP  OpenStreetMap  MapAction  IFRC  MINUSTHA  UNOSAT  World Bank  European Commission (EC)  the crowd  and many MANY more

3. 3 2000+ maps published in 75 days Haiti maps published on GDACS/VirturalOSOCC Around 500 maps in a week 40+ map providing entities Date Number of maps published

4. 4 What makes Haiti so special in this sense?  Data availability (field collected, aerial photos, satellite imagery)  Open source and community mapping  Use of social media (Twitter, Facebook, wikis)  Field presence of GIS staff  Integrated in response and recovery  Across and withing clusters Shelter  IDP camp monitoring  Baseline data collection  Risk mapping  Damage assessment  Link to reconstruction and development through PDNA

5. 5 CNIGS  Heavily affected by earthquake  Quickly back to operational capacity  Considerable data repository  National GIS mandate  Field assessments (damage to public infrastructure) in collaboration with UNOSAT  Capacity development

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7. 7 Geospatial Products (Timeframe) 12 Jan.22 Jan. 26 Feb Haiti EQ Situation maps Preliminary DA UN-EC-WB Comprehensive DA and Joint Blds DA Atlas 18 Feb.12 Mar. PDNA 17 Mar. S. Dom. Conf. Flash Appeal NY Conf. 31 Mar. UNOSAT/JRC/WB combined GIS database Field Validation (UNOSAT- CNIGS- JRC) April

8. 8 Available RS data Through the use of aerial photos provided by the WB, Google and NOAA and satellite imagery from GeoEye and Digitalglobe, detailed damage assessments of individual buildings was conducted by comparing pre ‐ earthquake satellite imagery to post ‐ earthquake aerial photos. Pre-Disaster Sat. Image Post-Disaster Aerial Photo

9. 9 UNOSAT DA Methodology Training areas within UNOSAT AOI were identified to define suitable damage level classes for RS DA analysis Assessed buildings through photo interpretation were then categorized into 4 main damage classes according to the European Macroseismic Scale-98 (EMS-98) definition: GRADE 5: Destruction All or most of building structure collapsed. Here: Collapsed/broken roof, walls destroyed (debris surrounding building) GRADE 4: Very heavy damage Part of building structure collapsed, such as part of roof or one or more fallen walls. Here: Wall fallen into street (bright debris) GRADE 3: Substantial to heavy damage Limited damage observed to building, or no damage observed but immediately adjacent to destroyed or very heavily damaged building. GRADE 1: No visible damage Assessed building does not appear to be damaged. Here: Centre building with brown roof seems intact. No debris or collapsed structure observed.

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11. 11 Since the beginning IOM support the Task force operation on the debris removal and damage assessment. Several maps have been provide to define the area of interest and to dispatch civil engineer. IOM, iMMAP

12. 12 DATA Entry Access/SQL database. 20 people involve in data entry Integrate OSM ID inside database. Integrate data from the CNIGS Make on OSM platform to get information quickly and integrate inside our database and make map. CAMP Registration and decongestion of the Major camps

13. 13 Need continuity in term of Imagery accessibility. The need image in the field don’t stop at the end of charter call. Last image used is from the 9 march and the previous one is from the 25 of january. With this imagery we pass in PaP to 460 camps 870 camps base on satellite imagery assessment (OCHA). CAMP Monitoring System

14. 14 Risk mapping over IDP camps

15. 15 OSM WikiProject Haiti - snapshot OSM GPS map extracts used by Search And Rescue Teams – day 1 OSM = roads core data set (OCHA Core Data sets check-list). 26 hours to get imagery released and 48 hours to get 1 st imagery loaded on the OSM platform available for tracing

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17. 17 World Bank aerial data collection Generate a preliminary assessment of damage for Haiti using satellite and aerial photography to inform the PDNA process and provide base date for reconstruction efforts.

18. 18 Very High Resolution Optical (15cm)

19. 19 54321 PORT-AU-PRINCE1128855167862614552529153316848650 Commercial24148835396424507625677670044 Downtown7824984495669717009419085 Industrial7091169939901103032810 Residential high density4006985777145663453603773192630 Residential low density1574402271403020881648201895348 Shanty243889418321264871529621668733 Grand Total1128855167862714552529153326848650 Cost in US$ per m 2 500 30010040 Total cost (MUS$)564.4275839.3135436.575691.5332273.946 Example of Damage Figures for Port au Prince: Number of buildings per class Damages per land use class Floor area per land use type and damage class allowing a monetary estimation of damages (approx. 2.2 billion US-$ for Port-au-Prince EC JRC-WB-UNOSAT joint assessment results

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21. 21 Conclusion GIS integrated into Haiti relief and recovery GIS in cluster support horizontal (same geographic information baseline data across clusters) vertical (cluster-specific GIS information management) Large focus is on shelter – use the capacity!

22. einar.bjorgo@unitar.org www.unitar/unosat.org