• Spectroscopy and Spectral Analysis
  • Vol. 30, Issue 8, 2065 (2010)
XIAO Xia1、*, SONG Wei-guo1, WANG Yan1, TU Ran1, LIU Shi-xing2, and ZHANG Yong-ming1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: Cite this Article
    XIAO Xia, SONG Wei-guo, WANG Yan, TU Ran, LIU Shi-xing, ZHANG Yong-ming. An Improved Method for Forest Fire Spot Detection Based on Variance Between-Class[J]. Spectroscopy and Spectral Analysis, 2010, 30(8): 2065 Copy Citation Text show less

    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.
    XIAO Xia, SONG Wei-guo, WANG Yan, TU Ran, LIU Shi-xing, ZHANG Yong-ming. An Improved Method for Forest Fire Spot Detection Based on Variance Between-Class[J]. Spectroscopy and Spectral Analysis, 2010, 30(8): 2065
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