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

Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu

doi:10.1117/1.3078426

1 January 2009 Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection

Wanting Wang, John J. Qu, Xianjun Hao, Yongqiang Liu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 3, Issue 1, 031502 (January 2009). https://doi.org/10.1117/1.3078426

Abstract

In the southeastern United States, most wildland fires are of low intensity. A substantial number of these fires cannot be detected by the MODIS contextual algorithm. To improve the accuracy of fire detection for this region, the remote-sensed characteristics of these fires have to be systematically analyzed. Using an adjusted algorithm, this study collected a database including 6596 remote-sensed fire pixels in 72 MODIS granules, of which 3809 fire pixels are missed by the MODIS contextual algorithm. The statistical distributions of the sensor-observed fire reflectance and brightness temperature at relevant spectral channels are analyzed. The study explains the reasons that the detection of low intensity 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 suggests several aspects which could improve regional detection of low intensity fires. The results indicate that 1) the R₂ threshold R₂ < 0.3 is still valid for detecting low intensity fires omitted by the MODIS contextual algorithm; 2) the threshold T₄ > 310 K is too high, and a lower threshold of T₄ > 293 K should be adopted instead; 3) the threshold Δ T > 10 K is also too high, and both algorithms that use it risk omitting small fires because of this threshold.

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Wanting Wang, John J. Qu, Xianjun Hao, and Yongqiang Liu "Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection," Journal of Applied Remote Sensing 3(1), 031502 (1 January 2009). https://doi.org/10.1117/1.3078426

Published: 1 January 2009

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