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LBA Ecology Land Cover – 23

Validation and comparison of Terra/MODIS active fire detections from INPE and UMd/NASA algorithms. LBA Ecology Land Cover – 23 Jeffrey T. Morisette 1 , Ivan Csiszar 2, Louis Giglio 2 Wilfrid Schroeder 3 , Doug Morton 2 , João Pereira 3 , Chris Justice 2 ,

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LBA Ecology Land Cover – 23

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  1. Validation and comparison of Terra/MODIS active fire detections from INPE and UMd/NASA algorithms LBA EcologyLand Cover – 23 Jeffrey T. Morisette1, Ivan Csiszar2, Louis Giglio2Wilfrid Schroeder3, Doug Morton2, João Pereira3, Chris Justice2, 1National Aeronautics and Space Administration, Greenbelt, Maryland, USA 2Universityof Maryland, College Park, Maryland, USA 3Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis, Brazilia, Brazil

  2. Acknowledgements • …special thanks to • Darrel Williams and Peter Griffith and the LBA-Eco project office • Diane Wickland for including this work into LBA-Ecology project • Heloisa Miranda and Alexandre Santos for collaboration on the Thermocouple data • Alberto Setzer for collaboration on implementing the INPE algorithm • Ruth Defries for continued collaboration on MODIS-related research • Mike Abrams and Leon Maldonado for assistance in acquiring ASTER imagery

  3. Background • IBAMA/PROARCO is charged with monitoring Brazilian fires • IBAMA posts “Hot Spot” detections from several satellites and algorithms. • MODIS provides “state of the art” fire detection, but needs to be validated • Two algorithms on the same sensor’s data and a high resolution sensor on the same satellite create and unique opportunity for this validation study

  4. Goals • Assess the accuracy of the 1 km fire product from the Moderate Resolution Imaging Spectroradiometer (MODIS) over the LBA-Study area • Compare the INPE and UMd algorithm as they relate to the ASTER fire detection

  5. MODIS Instrument (1/2) • “Moderate Resolution Imaging Spectroradiometer” • On board AM-1 (“Terra”) and PM-1 (“Aqua”) polar orbiters • Terra 10:30 & 22:30 local overpass • Aqua 01:30 & 13:30 local overpass

  6. MODIS Instrument (2/2) • 36 spectral bands covering 0.4 to 14.4 micrometers • Two 250 m bands • Five 500 m bands • Twenty nine 1 km bands • Enable comprehensive daily evaluation of land, ocean, and atmosphere

  7. Daily Global Browse

  8. ASTER imagery

  9. ASTER Characteristics • “Advanced Spaceborne Thermal Emission and Reflection Radiometer” • 14 channels • 4 visible and near-IR @ 15 m resolution, 8 bits • 6 SWIR @ 30 m resolution, 8 bits • 5 LWIR @ 90 m resolution,12 bits • 60 km swath width

  10. Roraima: prescribed burn, 19 Jan ASTER fire mask band 3 and 8 240, 30m pixels red = band 3, ~22 ha green & blue = band 8 Fire pixels shown in ASTER band3/band8 space

  11. ASTER fire detection Mask water pixels. If 8 < 0.04, a pixel is flagged as water and excluded from further processing. Identify obvious fire pixels. Pixels for which r > 2 and  > 0.2 are considered to be obvious fire pixels and are flagged as such. Identify candidate fire pixels. Pixels for which r > 1 and  > 0.1 are considered to be candidate fire pixels. - contextual tests 

  12. Omission and Commission error INPE (no UMDfires detection)

  13. ASTER/MODIS scatter plot

  14. UMd Omission error INPE UMD

  15. ASTER/MODIS scatter plot

  16. Logistic Regression UMd INPE

  17. Results from 22 ASTER scenes Larger circles are MODIS fires Red = high confidence Blue = lower confidence “Adjacency” index ASTER fire counts

  18. Matriz de Error B D A C

  19. Error matrix for any ASTER fire detection

  20. Error matrix For variable fire size Fires > .0009 km2 Fires > .045 km2 Fires > .090 km2

  21. Error Matrix figures …as a function of fire size

  22. Conclusions • ASTER fire detection algorithm is now established • Comparison of ASTER with MODIS fire products and possible and enlightening • Both UMd and INPE algorithm do a good job at detecting large fires • INPE has less error for large fires • UMd has less error for small fire & less likely to have false positives

  23. Questions? jeff.morisette@nasa.gov

  24. MODIS: UMd Algorithm • Bands used for fire algorithm • “T4”= • Channel 22: 3.96 µm, ≈ 330 K saturation • (lower noise, lower quantization error, but lower saturation) • - or - • Channel 21: 3.96 µm, ≈ 500 K saturation • (used when channel 22 saturates) • “T11” = • Channel 31: 11.0 µm, ≈ 400 K saturation

  25. MODIS: UMd Algorithm • T4 > 360 K • or • {T4 > mean(T4) + 3xStandardDeviationor T4 > 330 K} • and • {T4–T11>median(T4-T11) + 3xStandardDeviation(T4-T11) or T4-T11 > 25} • Then rejected if red and near-infrared channels have reflectance > 30% (to avoid false positives) • From: “The MODIS fire products”, C.O. Justice, L. Giglio et al., Remote Sensing of Environment 83(2002) 244-262.

  26. MODIS: INPE Algorithm channel 20 > 3000 and channel 09 < 3300

  27. Error Matrix figures …as a function of fire size

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