Technology Application |
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Remote sensing mapping for uni-temporal cross-region forest burned area based on fuzzy set theory |
ZHU Xi, QIN Xianlin, LIAO Jing |
Research Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China |
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Abstract It is very difficult to tackle the problems of the selection of optimal parameters and the determination of thresholds for the forest burned area mapping by using remote sensing data. In this paper, HJ-1B CCD and IRS data were combined to make a contribution to the spectral indices. An ordered weighting averaging (OWA)operator based fuzzy set theory was utilized to aggregate the positive evidence and negative evidence used to revise the positive information so as to reduce the commission error. Thermal infrared band was added to aggregate the negative evidence to test its validity. Then, the revised positive evidence was input for a regional growing algorithm to produce the result. The performance of the method was tested for two HJ-CCD/IRS images of Skovorodino in Russia and Xunke County in Heilongjiang Province in China. The results show that the overall accuracy is higher than 85% in both research areas, which indicates that the method proposed in this paper could meet the application need for burned area mapping.
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Keywords
Canny algorithm
road extraction
edge matching
remote sensing in mining area
surface mining system
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Issue Date: 21 October 2013
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