1 / 26

Renee Jacokes-Mancini Forest Service Southern Region Jess Clark & Kevin Megown USFS Remote Sensing Applications Cent

Hurricane Katrina Damage Assessment on Lands Managed by the Desoto National Forest using Multi-Temporal Landsat TM Imagery and High Resolution Aerial Photography. Renee Jacokes-Mancini Forest Service Southern Region Jess Clark & Kevin Megown USFS Remote Sensing Applications Center (RSAC).

rumor
Download Presentation

Renee Jacokes-Mancini Forest Service Southern Region Jess Clark & Kevin Megown USFS Remote Sensing Applications Cent

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Hurricane Katrina Damage Assessment on Lands Managed by the Desoto National Forest using Multi-Temporal Landsat TM Imagery and High Resolution Aerial Photography Renee Jacokes-Mancini Forest Service Southern Region Jess Clark & Kevin Megown USFS Remote Sensing Applications Center (RSAC) GeoSpatial Conference 2007 Portland, OR May 9, 2007

  2. Overview • Background of Hurricane Katrina damage • Need for damage assessment • Method use of assessment • Results • Recommendations

  3. Hurricane Katrina • Hurricane Katrina made landfall in Louisiana and Mississippi and caused extensive damage. • Landfall: August 29, 2005 • Strong Category 3 at landfall • Sustained winds of 111 to 130 mph • Costliest Atlantic Hurricane in U.S. history

  4. June 2005 September 2005 Water Damage

  5. Wind Damage

  6. Initial Forest Damage Assessments • Forest Inventory and Analysis (FIA) – September 2005 • Forest Health Protection (FHP) – November 2005 Initial assessments provided little explanation of damage severity or were based on few samples. Different method needed to meet National Forest management information requirements.

  7. New Damage Assessment • Hurricane Katrina made landfall in Louisiana and Mississippi and caused extensive damage. New damage assessment performed by RSAC • Utilizes multi-stage sampling and multiple scales of remotely-sensed imagery • Provides a statistically-defensible approach to mapping damage potential

  8. Desoto NF overlaid on path 21 row 39 Methods - Landsat • Multi-temporal Landsat imagery acquired • Pre-storm: Oct. 15, 2004 • Post-storm: Nov. 3, 2005 • WRS Path/Row: 21/39 • Converted to Reflectance • Other path/rows acquired but sampling performed only on 21/39

  9. Methods - Landsat • Normalized Difference Vegetation Index (NDVI) performed on pre- and post-storm Landsat • Change in NDVI calculated as a continuous dataset • ISODATA Unsupervised Classification performed on NDVI change product • Output: 12 class thematic image

  10. Urban/Ag Masked Out Post-storm Pre-storm Methods – Multi-stage Sample • Built-up, Urban, and Ag areas masked out of Landsat imagery • Those land use types can easily confuse the NDVI change • We are interested in damage to forest

  11. Methods - Photos • The Desoto NF sent RSAC over 400 scanned photos flown by FHTET during October, 2005 • 1:15,840 scale • Flown with Inertial Measurement Unit (IMU) • Photos scanned – 1/2 m pixels • Data compiled into Block Files for Leica Photogrammetry Suite (LPS) • Photos orthorectified using 30m DEM

  12. Methods - Sampling • 12-class raster NDVI change product converted to point coverage • Each point represented center of pixel • 10 points randomly selected from each class • 120 primary sampling units (PSUs) • Assessment done with this dataset to estimate variance and sample needs for whole study

  13. Methods - Sampling • Based off initial assessment, to reach a standard error of 2%, we needed to sample the following: Total: 423 Primary Sampling Units (PSUs)

  14. Methods - Sampling • 423 PSU locations chosen randomly Note: Top and west edges excluded because path 21 row 39 orbit excluded it from the Landsat acquisition.

  15. Size of Landsat pixel over digital photo Methods - Sampling Nearly 4,000 points interpreted for damage – no damage

  16. Methods - Sampling Size of Landsat pixel over digital photo

  17. Methods - Sampling • Digital Mylar – Image Interpreter (ArcMap extension) used to perform damage assessment • 3x3 grid (9 points) centered around PSU • All 9 points fit within one Landsat pixel • Assessed for damage – no damage • Damage = obvious thrown trees

  18. Methods - Analysis • Sample provided basis for % damage estimates with standard errors for each of the 12 NDVI change classes Overall 14.4% of Pts. Attributed as Damaged

  19. Strata Damage (%) Class 11 43.67 4 Class 7 34.10 Class 9 19.36 3 Class 4 18.44 Class 10 13.20 Class 12 12.44 2 Class 6 7.76 Class 3 7.29 Class 8 6.35 Class 2 1.24 1 Class 5 0.43 Class 1 0.00 Methods - Analysis • Student-Newman-Keuls (SNK) Test used to create 4 separable damage classes

  20. Results Class 1 – Lowest probability of damage Class 2 Class 3 Class 4 – Highest probability of damage

  21. Results • Based on the data, less damage than originally assumed was present on the Desoto Ranger District • Original Damage Projects • Final Damage/Harvest

  22. Scan images, compile into block files Photography acquisition begins Begin photo sampling Orthorectify photos Data Analysis Hurricane Day 1 8 10 14 18 22 25 NDVI change products created Landsat acquired Expected Time-Line Needs • Acquisition of aerial photography: Variable – days to weeks • Orthorectification and reprojection of photography: 2 days • Acquisition and processing of Landsat imagery: 2 days • Sampling photography for damage/no-damage: 3 days • Data analysis: 1 day

  23. Discussion • Data-driven damage assessment • Multi-stage sampling design an effective way to assess damage probability • Potential application for future events

  24. Discussion • Not statistical tested/No accuracy assessment • General guide to the savage crew to locate the most affected areas • Quick and efficient way to create damage assessment • Product can be used to help direct salvage and other management decisions

  25. Method Transfer to the Field • RSAC Steering Committee providing 30K • Method Transfer to the field • Texas National Forests • Development of “How to” Documents

  26. Questions For Further information contact: • Renee Jacokes-Mancini rjacokes@fs.fed.us (404) 347-2588 • Jess Clark jtclark@fs.fed.us (801) 975-3769

More Related