Your SlideShare is downloading. ×
  • Like
  • Save
Processing satellite imagery for mapping physical exposure globally
Upcoming SlideShare
Loading in...5

Thanks for flagging this SlideShare!

Oops! An error has occurred.


Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Processing satellite imagery for mapping physical exposure globally


Daniele EHRLICH, Stamatia HALKIA, Thomas KEMPER, Martino PESARESI, Pierre SOILLE …

Daniele EHRLICH, Stamatia HALKIA, Thomas KEMPER, Martino PESARESI, Pierre SOILLE

Joint Research Centre, European Commission, Italy, Republic of

Published in Education , Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads


Total Views
On SlideShare
From Embeds
Number of Embeds



Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

    No notes for slide


  • 1. Processing satellite imagery for mappingphysical exposure globallyEhrlich D., Halkia S., Kemper T., Pesaresi M., and Soille P.Session: Global exposure monitoring for multi-hazard riskassessments4TH INTERNATIONAL DISASTER AND RISKCONFERENCE - IDRC DAVOS 2012
  • 2. Why satellite imagery?• Imagery for quantifying physical exposure• Abundance of imagery• Exposure maps from imagery• Process large volume of data• Global – cities and rural areas• New processing systems in place
  • 3. Satellite imagerySatellite imagery to locate and quantify human settlements and physical exposure
  • 4. Why is Google Earth not sufficient?• Images are not Data enough  Data • Buildings, roads, trees …• We need numbers (digital maps)  Information • How many buildings? • What is the extent of Information settlements • How much is at risk?
  • 5. Where, how much, how many?Techniques:1. Manual encoding (above)2. Machine assisted (train a computer algorithm - automatic) next slides
  • 6. Lots of satellite imagery is availableOpen source Commercial data
  • 7. Human settlement derived from Sana’ from VHR imageryVery High Resolution
  • 8. Human Settlement derived from SPOT-5 The image is processed to generate a map that contains information on human settlements, i.e.Alger density of buildings, number of buildingsThis is just DATA Digital Map (yellow) This is INFORMATION
  • 9. Human settlement derived fromLandsat Settlement maps for 1.London 2.Delhi 3.Los Angeles 4.Paris 5.Roma 6.San Francisco 7.Jakarta 8.Madrid 9.Milan Each image shows 36 x 36 km All cities of the world could be mapped
  • 10. Urban sprawl (increase in exposure)
  • 11. New concept: Human settlement analysis and monitoring system• Take all imagery necessary• Use standardized algorithms that work across the globe on a number of image types• Put in place an infrastructure that can process imagery covering the entire Earth’s land masses
  • 12. Information flow for the globalVHR: Ikonos,QuickBird, human settlement system analysisWorld View… and monitoring systemHigh ResSPOT, CBERS Human Human Settlement PhysicalMedium Res Settlements Indices exposureLandsat (Global)Coarse Resi.e. Modis VulnerabilityInformationMODIS-UrbanLandscan
  • 13. VHR complexity: data size Number of pixels needed to cover 1 sq km 4,500,000 WorldView-1 P 4,000,000 3,500,000 3,000,000 QuickB. P 2,500,000 2,000,000 1,500,000 IKONOS P 1,000,000Landsat MSS Landsat TM Spot4 XS Spot4 P 500,000 Spot5 P 0 50 45 40 35 30 25 20 15 10 5 0 IRS-1 IKONOS MS QuickB MS Sensor spatial resolution (m)
  • 14. JRC GHSL 50K integration with other sources
  • 15. JRC GHSL 50K output
  • 16. Brazil, settlement mapImages (yellow) used toproduce the settlementmap
  • 17. China Settlement MapImages (yellow)used to produce thesettlement map
  • 18. Global – All settlementsSparse settlements as found in rural areas are often notaccounted for in exposure mapping
  • 19. New VHR GHSL Model Panchromatic image of Sana’a Yemen (8956×16384, 8-bit elements).Tree computation time (both): 50sec. Layer computation time: 17sec. No Free Parameter – blind computational allowed
  • 20. Earth Observation technology (satellite images) for exposure• Very rich source of information on the Earth surface• More sensors will be launched and more imagery will be available in the future• The detail of the imagery is adequate to map physical exposure globally• Extracting information is costly but new algorithm can facilitate the process• Computing power is no longer a limitation
  • 21. JRC will run two services for the community (from web portal)1. Information on demand • Send area of interest and receive information A. If coarser imagery is available A. Density of built up B. If Very High Resolution imagery is available A. Density of built up B. Number of buildings C. Average size of buildings2. Processing on demand • Send imagery, and receive the information
  • 22. Thank you for your attentionISFEREA ActionEuropean Commission • Joint Research CentreIPSC/Global Security & Crisis Management UnitTel. +39 0332 785648Email: