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MODERN TUNNELLING TECHNOLOGY 2021, Vol. 58 Issue (6) :31-37    DOI:
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Analysis on Land Surface Geothermal Spatial Distribution Characteristics of Long and Deep Tunnels Based on Landsat 8 Remote Sensing Images: A Case Study of Gaoligongshan Tunnel
(China Railway Southwest Research Institute Co., Ltd., Chengdu 611731)
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Abstract Taking Gaoligong Mountain Area as the study area, this paper is focused on quickly obtaining the spatial distribution characteristics of land surface temperature of long and deep tunnels. According to the Landsat 8 remote sensing images of the study area, the radiative transfer equation method is adopted to perform land surface temperature inversion, which is then compared with the results of single channel algorithm. The results show that: (1) the remote sensing method could be used to quickly and effectively obtain the land surface temperature in the study area,the geothermal spatial distribution conditions are consistent with the fault distribution and exposed hot spring distribution conditions revealed by the existing geological survey, and the ground temperature results obtained by two algorithms are relatively consistent; (2) in the study area, the geothermal resources are mainly distributed in Nujiang River Valley and Luxi-Zhefang Basin, and sporadic high-temperature reactions appear in some mountain areas. In Nujiang River Valley, the geothermal resources are distributed in a north-south belt along Nujiang Fault Zone,which is mainly governed by many deep and large faults in Gaoligong Mountain Area. In Luxi-Zhefang Basin, the geothermal resources are generally distributed in a strip from south-north to north-east in the middle of the basin and mainly governed by the Longling-Ruili Fault and the Basin topographies; (3) the different influences of solar ra? diation on sunny and shady slopes should be considered when the remote sensing method is used to explore geothermal distribution in complex mountain areas.
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HUA Xiaoming LUO Chenxi GOU Xiaojun ZHANG Haichao
KeywordsLandsat 8 image   Thermal infrared remote sensing   Land surface temperature   Single channel algo? rithm   Radiative transfer equation method     
Abstract: Taking Gaoligong Mountain Area as the study area, this paper is focused on quickly obtaining the spatial distribution characteristics of land surface temperature of long and deep tunnels. According to the Landsat 8 remote sensing images of the study area, the radiative transfer equation method is adopted to perform land surface temperature inversion, which is then compared with the results of single channel algorithm. The results show that: (1) the remote sensing method could be used to quickly and effectively obtain the land surface temperature in the study area,the geothermal spatial distribution conditions are consistent with the fault distribution and exposed hot spring distribution conditions revealed by the existing geological survey, and the ground temperature results obtained by two algorithms are relatively consistent; (2) in the study area, the geothermal resources are mainly distributed in Nujiang River Valley and Luxi-Zhefang Basin, and sporadic high-temperature reactions appear in some mountain areas. In Nujiang River Valley, the geothermal resources are distributed in a north-south belt along Nujiang Fault Zone,which is mainly governed by many deep and large faults in Gaoligong Mountain Area. In Luxi-Zhefang Basin, the geothermal resources are generally distributed in a strip from south-north to north-east in the middle of the basin and mainly governed by the Longling-Ruili Fault and the Basin topographies; (3) the different influences of solar ra? diation on sunny and shady slopes should be considered when the remote sensing method is used to explore geothermal distribution in complex mountain areas.
KeywordsLandsat 8 image,   Thermal infrared remote sensing,   Land surface temperature,   Single channel algo? rithm,   Radiative transfer equation method     
Cite this article:   
HUA Xiaoming LUO Chenxi GOU Xiaojun ZHANG Haichao .Analysis on Land Surface Geothermal Spatial Distribution Characteristics of Long and Deep Tunnels Based on Landsat 8 Remote Sensing Images: A Case Study of Gaoligongshan Tunnel[J]  MODERN TUNNELLING TECHNOLOGY, 2021,V58(6): 31-37
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