Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection

Abstract

In the southeastern United States, most wildland fires are of low intensity. Asubstantial number of these fires cannot be detected by the MODIS contextual algorithm. Toimprove the accuracy of fire detection for this region, the remote-sensed characteristics ofthese fires have to be systematically analyzed. Using an adjusted algorithm, this studycollected a database including 6596 remote-sensed fire pixels in 72 MODIS granules, ofwhich 3809 fire pixels are missed by the MODIS contextual algorithm. The statisticaldistributions of the sensor~observed fire reflectance and brightness temperature at relevantspectral channels are analyzed. The study explains the reasons that the detection of lowintensity fires by the MODIS contextual algorithm is significantly influenced by view angles,especially when view angles are greater than 40 degrees. This paper discusses and suggestsseveral aspects which could improve regional detection of low intensity fires. The resultsindicate that I) the R2 threshold R2 < 0.3 is still valid for detecting low intensity fires omittedby the MODIS contextual algorithm; 2) the threshold T~ > 310 K is too high, and a lowerthreshold of T, > 293 K should be adopted instead; 3) the threshold 1>T> 10 K is also toohigh, and both algorithms that use it risk omitting small fires because of this threshold.

Citation

Wang, W.; Qu, J.J.; Hao, X.; Liu, Y. 2009. Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection. Journal of Applied Remote Sensing Vol.3.