Research on Multi-source Remote Sensing Detection of Concealed Fire Sources in Coalfields

WANG Yunjia; YUAN Gang; WANG Teng; LIU Jinglong; ZHAO Feng; FENG Han; DANG Libo; PENG Kai; ZHANG Leixin

doi:10.13203/j.whugis20220184

Volume 47 Issue 10

Oct. 2022

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Geomatics and Information Science of Wuhan University > 2022 > 47(10): 1651-1661. > DOI: 10.13203/j.whugis20220184

WANG Yunjia, YUAN Gang, WANG Teng, LIU Jinglong, ZHAO Feng, FENG Han, DANG Libo, PENG Kai, ZHANG Leixin. Research on Multi-source Remote Sensing Detection of Concealed Fire Sources in Coalfields[J]. Geomatics and Information Science of Wuhan University, 2022, 47(10): 1651-1661. DOI: 10.13203/j.whugis20220184

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Research on Multi-source Remote Sensing Detection of Concealed Fire Sources in Coalfields

WANG Yunjia^{1, 2,},
YUAN Gang^{1, 2},
WANG Teng^{1, 2},
LIU Jinglong^{1, 2},
ZHAO Feng^{1, 2},
FENG Han^{1, 2},
DANG Libo^{1, 2},
PENG Kai^{1, 2},
ZHANG Leixin^{1, 2}

1.
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
2.
Key Laboratory of Land Environment and Disaster Monitoring, Ministry of Natural Resources, China University of Mining and Technology, Xuzhou 221116, China

Funds:

The National Natural Science Foundation of China 41874044

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Author Bio:
WANG Yunjia, PhD, professor, specializes in land environment and disaster monitoring. E-mail: wyj4139@cumt.edu.cn
Received Date: May 21, 2022
Available Online: June 20, 2022
Published Date: October 04, 2022

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Abstract

Abstract

Underground coal fire is widely distributed and repeatedly treated, causing waste of resources and ecological damage. China is the country with the most serious coal spontaneous combustion disaster in the world, 80% of coal seams have the tendency to spontaneous combustion. Rapid, comprehensive, timely and accurate detection of hidden fire sources in coalfields is the basis and prerequisite for fire prevention, extinguishing and ecological management. Multi-source remote sensing has a great potential for the applications, but it needs to penetrate the surface and go deep underground, and there are many bottlenecks to be solved. Firstly, the problem of multi-source remote sensing detection of hidden fires in coalfields is abstracted into the key nodes of same source (same underground spontaneous combustion source), multi-phenomenon (various abnormal phenomena formed on the surface), multi-image (photographed by multi-source remote sensing, including a variety of surface image of abnormal information). Meanwhile, the research chain of multiple phenomena is analyzed, which includes the same source, the phenomenon to image mapping, the transmission from source to phenomenon, and the multiple image recognition source. On these basis, the technical bottleneck of multi-source remote sensing detection of concealed fire sources in coalfields is discussed. Secondly, based on the research examples of concealed fire detection in coal fire areas of Fukang, Miquan and Bao'an in the Xinjiang Uygur Autonomous Regions, China, we give the research progress and effects of polarized time-series interferometric synthetic aperture radar (InSAR) fire area deformation detection, spatio-temporal temperature threshold method fire area delineation, multi-source satellite remote sensing fire area identification, and unmanned aerial vehicle fire area monitoring experiment. Finally, the development direction of integrating multi-source satellite remote sensing images and space-sky-ground-mine cooperative perception cognitions is prospected.
- multi-source remote sensing,
- coalfield spontaneous combustion,
- concealed fire source,
- multiple image recognition source,
- detection

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References

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