GIS systems in Haiti Shelter focus Shelter Meeting 10a, Geneva 27-28 May 2010 Einar Bjorgo.
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Transcript of GIS systems in Haiti Shelter focus Shelter Meeting 10a, Geneva 27-28 May 2010 Einar Bjorgo.
GIS systems in Haiti
Shelter focus
Shelter Meeting 10a, Geneva 27-28 May 2010
Einar Bjorgo
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Unpresedented number of mapping efforts and Geographic Information System (GIS) initiatives
Actors include
CNIGS (Haiti National Mapping Agency)OCHAIOMWFPiMMAPOpenStreetMap MapActionIFRCMINUSTHAUNOSATWorld BankEuropean Commission (EC)the crowdand many MANY more
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2000+ maps published in 75 days
Haiti maps published on GDACS/VirturalOSOCC
Around 500 maps in a week40+ map providing entities
Date
Nu
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of
map
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ub
lish
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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
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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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Geospatial Products (Timeframe)
12 Jan. 22 Jan. 26 Feb
Haiti EQ
Situation maps Preliminary DA
UN-EC-WBComprehensive DAand Joint Blds DA
Atlas
18 Feb. 12 Mar.
PDNA
17 Mar.
S. Dom.Conf.
FlashAppeal NY
Conf.
31 Mar.
UNOSAT/JRC/WBcombined GIS database
Field Validation (UNOSAT- CNIGS- JRC)
April
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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
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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 damagePart 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 damageLimited damage observed to building, or no damage observed but immediately adjacent to destroyed or very heavily damaged building.
GRADE 1: No visible damageAssessed 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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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
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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
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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
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Risk mapping over IDP camps
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OSM WikiProject Haiti - snapshot
OSM GPS map extracts used by Search And Rescue Teams – day 1OSM = roads core data set (OCHA Core Data sets check-list).26 hours to get imagery released and 48 hours to get 1st imagery loaded on the OSM platform available for tracing
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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.
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Very High Resolution Optical (15cm)
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5 4 3 2 1PORT-AU-PRINCE 1128855 1678626 1455252 915331 6848650Commercial 241488 353964 245076 256776 70044Downtown 78249 84495 66971 70094 19085Industrial 7091 16993 9901 10303 2810Residential high density 400698 577714 566345 360377 3192630Residential low density 157440 227140 302088 164820 1895348Shanty 243889 418321 264871 52962 1668733Grand Total 1128855 1678627 1455252 915332 6848650
Cost in US$ per m2 500 500 300 100 40Total cost (MUS$) 564.4275 839.3135 436.5756 91.5332 273.946
Example of Damage Figures for Port au Prince:• Number of buildings per class• Damages per land use class• Floor area per land use type and damage class allowing a monetary estimation of damages (approx. 2.2 billion US-$ for Port-au-Prince
EC JRC-WB-UNOSAT joint assessment results
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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!
[email protected]/unosat.org