An automatic identification algorithm for wildfire occurrences near transmissionline corridors based on spatio-temporal context
DOI：DOI: 10.19783/j.cnki.pspc.211593
Key Words:Himawari-8  wildfire near transmission lines  spatio-temporal contextual  threshold  potential fire spot
Author NameAffiliation
WANG Kaizheng 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
FU Yitong 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
QIAN Guochao 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
ZHOU Fangrong 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
WEN Gang 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
LI Lulu SHAN Jieshan 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
SHAN Jieshan 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
WANG Feipeng 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
LI Jian 1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 605504, China
2. Electric Power Research Institute of Yunnan Electric Power Company, Kunming 650217, China
3. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 430074, China 
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Abstract:The traditional polar-orbit satellite with low-frequency observations and a fixed observation time is intractable to real-time monitoring for a specific region. Accordingly, a spatio-temporal contextual algorithm for continuous monitoring of wildfires near transmission lines is provided by the Himawari-8 (H-8) geostationary satellite. First, based on the difference in sensitivity of the mid-infrared and thermal infrared bands to the fire spots, the absolute and potential fire spots are determined by a fixed-threshold algorithm. Then, the flame pixels are identified by comparing the ratios between the channel value, mean, and standard deviation of the mid-infrared and thermal infrared from space. Also, persistent fire spots can be located by taking advantage of the high-frequency observation capability of H-8 in conjunction with the fire occurrence probability in terms of time. The proposed technique has been applied to the wildfire monitoring of transmission lines in a provincial power grid in southern China, boosting the accuracy rate to 72.5% and lowering the missing alarm rate to 43.9%, respectively. The current study results are significantly superior to the conventional contextual fire detection algorithm and fixed threshold algorithm. This work is supported by the National Natural Science Foundation of China (No. 52107017, No. 52177016, and No. 52130707).
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