MODIS Fire Product Collection 6 Improvements Louis Giglio 1, Wilfrid Schroeder 1, Ivan Csiszar 2, Chris Justice 1 1 University of Maryland 2 NOAA NESDIS.

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Presentation transcript:

MODIS Fire Product Collection 6 Improvements Louis Giglio 1, Wilfrid Schroeder 1, Ivan Csiszar 2, Chris Justice 1 1 University of Maryland 2 NOAA NESDIS

Collection 6 Algorithm Refinements Processing extended to oceans and other large water bodies – Detect off-shore gas flaring Reduce false alarms in Amazon caused by small forest clearings Dynamically adjust potential fire thresholds – Detect smaller fires Improved cloud mask Assorted minor improvements

Collection 5

Collection 6

Deepwater Horizon Offshore Drilling Rig Fire Terra MODIS :05 (21 April 2010) C6 Fire Mask True Color

C5C6 C6 Forest Clearing Rejection-Test False color ASTER imagery superimposed with approximate edges of MODIS pixels (black grid). MODIS fire pixels are outlined in red.

C6 Dynamic Potential-Fire Thresholds Detection algorithm uses various thresholds to quickly identify obvious non-fire pixels. These are known as “potential fire thresholds”. Prior to Collection 6, fixed values were used for the potential fire thresholds, and these were applied globally. However, these thresholds really should vary with scan angle, location, land cover type, season, etc. For Collection 6, the potential fire thresholds are set dynamically.

C6 Dynamic Potential-Fire Threshold Examples

Collection 6 Higher-Level Product Refinements 0.25° CMG product New CMG product layers – fire persistence Minor Level 3 product refinements