Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/112886
Title: New methods of active fire detection using MODIS data
Authors: Liew, S.C. 
Lim, A. 
Kwoh, L.K. 
Keywords: Forest fire
Hot spots
MODIS
Stochastic model
Target detection
Issue Date: 2005
Citation: Liew, S.C.,Lim, A.,Kwoh, L.K. (2005). New methods of active fire detection using MODIS data. Asian Association on Remote Sensing - 26th Asian Conference on Remote Sensing and 2nd Asian Space Conference, ACRS 2005 1 : 411-415. ScholarBank@NUS Repository.
Abstract: Active fire detection using satellite thermal sensors usually involves thresholding the detected brightness temperature in several bands. The frequently used features for fire detection are the brightness temperature in the 4-micron wavelength band (T4) and the brightness temperature difference between the 4-micron and 11-micron bands (dT=T4-T11). The thresholds used are determined empirically without any theoretical considerations, and thus may not be optimal for a given fire detection task. In this paper, we discuss a new approach in active fire detection based on a stochastic model for target detection. This approach considers the probability density functions of the fire and background pixels and optimal thresholds are derived depending on the specific objectives of the detection tasks. For example, the optimal threshold can be found by minimizing a cost function which is a weighted sum of the omission and commission errors. Alternatively, the threshold can also be derived based on the maximum likelihood criterion. The implementation of the new methods and the results of comparison with the conventional algorithms will be described.
Source Title: Asian Association on Remote Sensing - 26th Asian Conference on Remote Sensing and 2nd Asian Space Conference, ACRS 2005
URI: http://scholarbank.nus.edu.sg/handle/10635/112886
ISBN: 9781604237511
Appears in Collections:Staff Publications

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