Detecting Geothermal Anomalies Using Multi-Temporal Thermal Infrared Remote Sensing Data in the Damxung–Yangbajain Basin, Qinghai–Tibet Plateau

Author:

Li Xiao12,Jiang Guangzheng12ORCID,Tang Xiaoyin3,Zuo Yinhui12ORCID,Hu Shengbiao45,Zhang Chao12,Wang Yaqi45,Wang Yibo45ORCID,Zheng Libo6

Affiliation:

1. College of Energy, Chengdu University of Technology, Chengdu 610059, China

2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu 610059, China

3. Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China

4. State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China

5. University of Chinese Academy of Sciences, Beijing 100101, China

6. The First Institute of Hydrology and Engineering Geological Prospecting Anhui Geological Prospecting Bureau, Bengbu 233000, China

Abstract

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.

Funder

Natural Science Foundation of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference71 articles.

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