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, 1 National Aeronautics and Space Administration, Greenbelt, Maryland, USA 2 Universityof Maryland, College Park, Maryland, USA 3 Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis, Brazilia, Brazil

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

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

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

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

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

Daily Global Browse

ASTER imagery

ASTER Characteristics “Advanced Spaceborne Thermal Emission and Reflection Radiometer” 14 channels –4 visible and 15 m resolution, 8 bits –6 30 m resolution, 8 bits –5 90 m resolution,12 bits 60 km swath width

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

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

Omission and Commission error INPE (no UMD fires detection)

ASTER/MODIS scatter plot

UMd Omission error INPE UMD

ASTER/MODIS scatter plot

UMd INPE Logistic Regression

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

Matriz de Error A B C D

Error matrix for any ASTER fire detection

Error matrix For variable fire size Fires >.0009 km 2 Fires >.045 km 2 Fires >.090 km 2

Error Matrix figures …as a function of fire size

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

Questions?

MODIS: UMd Algorithm Bands used for fire algorithm “T 4 ”= –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) “T 11 ” = –Channel 31: 11.0 µm, ≈ 400 K saturation

MODIS: UMd Algorithm T 4 > 360 K or {T 4 > mean (T 4 ) + 3x StandardDeviation or T 4 > 330 K} and {T 4 –T 11 > median (T 4 -T 11 ) + 3x StandardDeviation (T 4 -T 11 ) or T 4 -T 11 > 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)

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

Error Matrix figures …as a function of fire size