光谱学与光谱分析 |
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An Improved Method for Forest Fire Spot Detection Based on Variance Between-Class |
XIAO Xia1,SONG Wei-guo1,WANG Yan1,TU Ran1,LIU Shi-xing2 ,ZHANG Yong-ming1* |
1. State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027, China 2. Hefei University of Technology, Hefei 230027, China |
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Abstract 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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Received: 2009-09-16
Accepted: 2009-12-09
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Corresponding Authors:
ZHANG Yong-ming
E-mail: zhangym@ustc.edu.cn
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