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Remote sensing of natural resources

Hurricane Katrina Damage Analysis. Remote sensing of natural resources. Alex Stern and William Tran. Overview. Assess the flood extent and impact created by Hurricane Katrina in New Orleans Examining Orleans Parish. Duke University. Initial Steps. Collect Data

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Remote sensing of natural resources

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  1. Hurricane Katrina Damage Analysis Remote sensing of natural resources Alex Stern and William Tran

  2. Overview • Assess the flood extent and impact created by Hurricane Katrina in New Orleans • Examining Orleans Parish Duke University

  3. Initial Steps • Collect Data • Landsat 5 images from August 25th, 2005 and September 7th, 2005 • Extract to Orleans Parish using Arc Map, Parish shapefile

  4. Classification • Supervised classification for both images • Landsat 5 bands 1,2,3,4, and 7 • Five land cover classes • Urban, Vegetation, Wetland, Water, and Flooded Urban

  5. Accuracy Assessment 2005 NAIP 2m orthophoto mosaic Class Reference Classified Number Producers Users Name Totals Totals Correct Accuracy Accuracy Class 0 38 54 38 --- --- Urban 16 25 10 62.50% 40.00% Vegetation 38 20 20 52.63% 100.00% Wetlands 15 24 11 73.33% 45.83% Flooded 1 0 0 --- --- Water 42 27 27 64.29% 100.00% Overall Classification Accuracy = 70.67% Overall Kappa Statistics = 0.6291  Class Name Kappa Class 0 0.6032 Urban 0.3284 Vegetation 1.0000 Wetlands 0.3981 Flooded 0.0000 Water 1.0000 *No accuracy assessment performed on post-storm image

  6. Rough Estimate

  7. Tabulated Data

  8. Flooded Urban

  9. Urban to Vegetation

  10. Water to Wetlands

  11. Tabulated Data

  12. Change Detection • 37 sq miles of flooded urban • 54 sq miles of flooded land • Increase of water and vegetation • Urban class lost 56 sq. miles • Evaluated over total land area: • 134,585 persons displaced, 16,697 housing units damaged • Evaluated over urban land area: • 281,332 persons displaced, 34,916 housing units damaged • Loss of wetlands, errors • 4 sq miles of wetlands changed to urban

  13. Problems and Limitations • Inaccuracy of classifications • Inaccuracy of census data interpretation and analysis • Limitation of area analyzed • Technical Errors • ArcMap conversions • Differences in shapefiles • Multiple extractions

  14. Real World Application • FEMA • Military • Insurance rates

  15. Questions? NASA/Jeff Schmaltz, MODIS

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