GIS systems in Haiti Shelter focus Einar Bjorgo

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

2 Unpresedented number of mapping efforts and Geographic Information System (GIS) initiatives Actors include §CNIGS (Haiti National Mapping Agency) §OCHA §IOM §WFP §i. MMAP §Open. Street. Map §Map. Action §IFRC §MINUSTHA §UNOSAT §World Bank §European Commission (EC) §the crowd §and many MANY more

Ja n 14 -10 -Ja n 16 -10 -Ja n 18 -10 -Ja n 20 -10 -Ja n 22 -10 -Ja n 24 -10 -Ja n 26 -10 -Ja n 28 -10 -Ja n 30 -10 -Ja n 1 - 10 Fe b 3 - 10 Fe b 5 - 10 Fe b 7 - 10 Fe b 9 - 10 Fe b 11 -10 -F eb 13 -10 -F eb 15 -10 -F eb 17 -10 -F eb 19 -10 -F eb 21 -10 -F eb 23 -10 -F eb 25 -10 -F eb 27 -10 -F eb 1 - 10 M ar 3 - 10 M ar 5 - 10 M ar 7 - 10 M ar 9 - 10 M a 11 r-10 -M ar -1 0 12 - Number of maps published 3 120 100 80 Haiti maps published on GDACS/Virtural. OSOCC Around 500 maps in a week 40+ map providing entities 60 40 20 0 Date 2000+ maps published in 75 days

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 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

6

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

8 Available RS data Through the use of aerial photos provided by the WB, Google and NOAA and satellite imagery from Geo. Eye 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 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 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. 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 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 5: Destruction All or most of building structure collapsed. Here: Collapsed/broken roof, walls destroyed (debris surrounding building)

10

11 IOM, i. MMAP 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.

12 CAMP Registration and decongestion of the Major camps 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.

13 CAMP Monitoring System 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 Pa. P to 460 camps 870 camps base on satellite imagery assessment (OCHA).

14 Risk mapping over IDP camps

OSM Wiki. Project Haiti - snapshot 15 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 ava for tracing

16

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 Very High Resolution Optical (15 cm)

19 EC JRC-WB-UNOSAT joint assessment results 70000 Number Commercial Industrial 7% Downtown 2% 0% of Damaged Buildings per EMS-98 Class 62693 60000 Slum 39% 50000 40000 30000 20000 15257 9902 12351 6699 10000 0 5 4 3 4 1678626 353964 84495 16993 577714 227140 418321 1678627 2 Residential low density 16% 1 PORT-AU-PRINCE Commercial Downtown Industrial Residential high density Residential low density Shanty Grand Total 5 1128855 241488 78249 7091 400698 157440 243889 1128855 3 1455252 245076 66971 9901 566345 302088 264871 1455252 2 915331 256776 70094 10303 360377 164820 52962 915332 1 6848650 70044 19085 2810 3192630 1895348 1668733 6848650 Cost in US$ per m 2 Total cost (MUS$) 500 300 564. 4275 839. 3135 436. 5756 100 91. 5332 40 273. 946 Residential high density 36% Example of Damage Figures for Port au Prince: • Number of buildings per class • Damages per land use class • Floor area per land use type and damage class allowing a monetary estimation of damages (approx. 2. 2 billion US-$ for Port-au-Prince

20

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!

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