Volume 27 Issue 1
Feb.  2021
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XIN Lei, LIU Xinxing, ZHANG Bin, 2021. Land surface temperature retrieval and geothermal resources prediction by remote sensing image: A case study in the Shijiazhuang area, Hebei province. Journal of Geomechanics, 27 (1): 40-51. DOI: 10.12090/j.issn.1006-6616.2021.27.01.005
Citation: XIN Lei, LIU Xinxing, ZHANG Bin, 2021. Land surface temperature retrieval and geothermal resources prediction by remote sensing image: A case study in the Shijiazhuang area, Hebei province. Journal of Geomechanics, 27 (1): 40-51. DOI: 10.12090/j.issn.1006-6616.2021.27.01.005

Land surface temperature retrieval and geothermal resources prediction by remote sensing image: A case study in the Shijiazhuang area, Hebei province

doi: 10.12090/j.issn.1006-6616.2021.27.01.005
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  • Received: 2020-11-09
  • Revised: 2021-01-10
  • Published: 2021-02-28
  • Thermal infrared remote sensing technology can retrieve land surface temperature information, which has played an important role in the prediction of geothermal resources. Based on the geothermal accumulation theory of the North China Plain, the mono-window algorithm was used to retrieve the land surface temperature of the Shijiazhuang area on March 6, 2015. Combined with the night thermal infrared images, remote sensing structure interpretation results and residual gravity anomaly data, through the comprehensive analysis and mutual demonstration, one upland convection-type and two sedimentary basin-type prospective areas were delineated, whose formation modes were convection and conduction respectively. In Sigou Village of Pingshan County, the land surface temperature is higher than that of the surrounding land features day and night, and the residual gravity anomaly data confirm the presence of NE faults in this area. Therefore, it is inferred that this area is a geothermal field formed by faults as water and heat conduction channels connecting the surface and the deep crustal heat source. The Gaocheng-Wuji area and Mayu-Huanmadian area are interpreted as deep uplift structures base on the residual gravity anomaly data, and there are hidden faults passing through, suggesting that this area is a geothermal field formed by the heat transfer and collection from the hidden faults to the uplift. This study is a geothermal resource prediction that based on the geothermal accumulation theory and the comprehensive analysis of remote sensing technology and geological and geophysical data. The prediction of target area is geologically interpretable and more in line with the understanding of geothermal accumulation.

     

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