An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States
✍ Scribed by Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu; William T. Sommers
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 817 KB
- Volume
- 108
- Category
- Article
- ISSN
- 0034-4257
No coin nor oath required. For personal study only.
✦ Synopsis
Traditional fire detection algorithms mainly rely on hot spot detection using thermal infrared (TIR) channels with fixed or contextual thresholds. Three solar reflectance channels (0.65 μm, 0.86 μm, and 2.1 μm) were recently adopted into the MODIS version 4 contextual algorithm to improve the active fire detection. In the southeastern United States, where most fires are small and relatively cool, the MODIS version 4 contextual algorithm can be adjusted and improved for more accurate regional fire detection. Based on the MODIS version 4 contextual algorithm and a smoke detection algorithm, an improved algorithm using four TIR channels and seven solar reflectance channels is described. This approach is presented with fire events in the southeastern United States. The study reveals that the T 22 of most small, cool fires undetected by the MODIS version 4 contextual algorithm is lower than 310 K. The improved algorithm is more sensitive to small, cool fires in the southeast especially for fires detected at large scan angles.