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Remote sensing of natural resources

Detailed examination of the impact of Hurricane Katrina in New Orleans using Landsat 5 imagery and classification techniques. Analysis includes flood extent, land cover changes, accuracy assessments, and real-world applications.

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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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