An Improved Method for Forest Fire Spot Detection Based on Variance Between-Class
An improved method using variance between-class and smoke plume mask is described. The brightness temperature threshold of potential fire pixels was adjusted to be 305 K. Based on the variance between-class of TIR channel brightness temperature and a smoke plume detection algorithm, the improved algorithm can separate the hot fire spots from the background and seek out the cool fire spots, respectively, with suitable thresholds of variance between-class. This algorithm has been used in the forest fires that happened in Fujian province and Heilongjiang province. Study shows that detection results with the algorithm are more satisfactory. It is adapted in different environments and can be more accurately detected the high-temperature fire spot and the smoder at low temperature. It increases the ability and accuracy to detect fire spots.
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Document Type: Research Article
Publication date: 2010-08-01
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