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

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.

Advances in Thermal Infrared Remote Sensing Technology for Geothermal Resource Detection

“…This technique adjusts surface temperature measurements to reflect genuine geothermal conditions rather than artifacts caused by variations in topography. Li et al ( 2023) introduced an innovative approach for efficiently calculating the multi-temporal LST in the Damxung-Yangbajing basin of the Qinghai-Tibet Plateau using Google Earth Engine (GEE) [59]. This methodology integrates terrain correction, elevation adjustment, and multi-temporal sequence analysis to discern geothermal anomaly signals.…”

“…(1) The long-term series of ground temperature anomaly observations play a significant role in enhancing the accuracy of geothermal resource detection using TIR remote sensing [57,59,67]. Initially, these observations contribute to the compilation of a comprehensive ground temperature database, thereby furnishing a critical benchmark against which remotely sensed surface temperature retrievals can be validated and refined.…”

“…This integrated approach allows for comparative analyses that can pinpoint regions exhibiting geothermal anomalies, thus facilitating the accurate localization of geothermal resource distributions. Furthermore, leveraging such data enables researchers to delve deeper into the actual potential and size of geother-mal reserves through the examination of parameters such as geothermal gradients and associated variables [59,87]. (2) The current research commonly employs global or local threshold methods to extract high-temperature anomalies from remote sensing data and combines these with regional geological structural characteristics for delineating geothermal anomaly zones [49,53,62].…”