Detecting Geothermal Anomalies Using Multi-Temporal Thermal Infrared Remote Sensing Data in the Damxung-Yangbajain Basin, Qinghai-Tibet Plateau
Detecting Geothermal Anomalies Using Multi-Temporal Thermal Infrared Remote Sensing Data in the Damxung-Yangbajain Basin, Qinghai-Tibet Plateau
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DOI：
10.3390/rs15184473
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发表时间：
2023-09
期刊：
影响因子：
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通讯作者：
Xiao Li;G. Jiang;Xiaoyin Tang;Y. Zuo;Shengbiao Hu;Chao Zhang;Yaqi Wang;Yibo Wang;Libo Zheng
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文献类型：
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作者：
Xiao Li;G. Jiang;Xiaoyin Tang;Y. Zuo;Shengbiao Hu;Chao Zhang;Yaqi Wang;Yibo Wang;Libo Zheng
地热能是存在于地球内部的一种生态友好的可再生地下热能来源。通过利用这些地层，流体可以被引导以加热上面的岩层，从而导致显着更高的地表温度（LST）。然而，LST读数受到太阳辐射，周期性变化和降水等各种因素的影响，这些因素可以掩盖地热引起的温度异常。为了解决这些问题，突出地热引起的LST异常，本文提出了一种方法来有效和快速地计算青藏高原当雄-羊八井盆地的多时相LST杠杆作用。该方法结合地形校正、高度校正和多时相序列比较来提取热异常信号。现有的地热现象被用作进一步完善方法的基准。结果表明，年平均冬季LST是地热异常信号的敏感指示器。2015年至2020年间的年平均冬季LST变化范围为-14.7 °C至26.7 °C，研究区域的平均气温为8.6 °C。经过海拔校正和水体去除后，年平均冬季LST变化范围为−22.1 °C至23.3 °C，平均值为6.2 °C。结合断层的分布和冬季年平均地表温度的结果，本研究划定的地热潜力区主要位于念青唐古拉山南麓的断裂带周围。潜在地热区的地表温度较高，为12.6 °C至23.3 °C。这些潜在区向东北方向延伸，热异常幅度高达19.6%。地热潜力面积占整个研究区的8.2%。结果表明，该方法成功地识别了部分已知地热田，并为未来的研究指出了最佳点。这项研究强调，利用多时相冬季LST是一种有效的和成本效益的方法，在高原环境中勘探地热资源。
Geothermal energy is an eco-friendly, renewable source of underground thermal energy that exists in the interior of the earth. By tapping into these formations, fluids can be channeled to heat the rock formations above, resulting in a significantly higher land surface temperature (LST). However, LST readings are influenced by various factors such as sun radiation, cyclical variations, and precipitation, which can mask the temperature anomalies caused by geothermal heat. To address these issues and highlight the LST anomalies caused by geothermal heat, this paper proposes a methodology to efficiently and quickly calculate the multi-temporal LST leveraging of the Google Earth Engine (GEE) in the Damxung–Yangbajain basin, Qinghai–Tibet Plateau. This method incorporates terrain correction, altitude correction, and multi-temporal series comparison to extract thermal anomaly signals. The existing geothermal manifestations are used as a benchmark to further refine the methodology. The results indicate that the annual mean winter LST is a sensitive indicator of geothermal anomaly signals. The annual mean winter LST between 2015 and 2020 varied from −14.7 °C to 26.7 °C, with an average of 8.6 °C in the study area. After altitude correction and water body removal, the annual mean winter LST varied from −22.1 °C to 23.3 °C, with an average of 6.2 °C. When combining the distribution of faults with the results of the annual mean winter LST, this study delineated the geothermal potential areas that are located predominantly around the fault zone at the southern foot of the Nyainqentanglha Mountains. Geothermal potential areas exhibited a higher LST, ranging from 12.6 °C to 23.3 °C. These potential areas extend to the northeast, and the thermal anomaly range reaches as high as 19.6%. The geothermal potential area makes up 8.2% of the entire study area. The results demonstrate that the approach successfully identified parts of known geothermal fields and indicates sweet spots for future research. This study highlights that utilizing the multi-temporal winter LST is an efficient and cost-effective method for prospecting geothermal resources in plateau environments.