Detection and constraints of geothermal latent heat zones under the complex terrain of the Western Sichuan Plateau: A fusion of multi-source temporal remote sensing data

Abstract

Geothermal energy is a sustainable and renewable resource with significant potential, particularly in regions with complex topography, such as high plateaus. However, accurately detecting geothermal anomalies in these areas presents challenges due to the influence of topographic factors and the resolution limitations of remote sensing data. To address these challenges, this study proposes a novel method that integrates multi-source and multi-temporal remote sensing data. The method leverages the high temporal resolution of MODIS, the high spatial resolution of Landsat 8, and topographic parameters derived from ALOS data. By combining dynamic multi-temporal thresholding and topographic correction, the approach effectively distinguishes geothermal signals from pseudo-thermal anomalies induced by solar radiation. The results demonstrate that the integration of multi-source remote sensing data enables the accurate identification of fine-scale thermal anomalies, consistent with the regional tectonic heat-control mechanisms. Topographic factors, including slope, aspect, and hillshade, are shown to significantly influence the spatial distribution of surface temperature. Following topographic correction, the model eliminates 36 %–45 % of pseudo-thermal anomaly areas, with high validation accuracy against actual hot spring locations. These findings underscore the critical importance of topographic correction in geothermal anomaly detection. By effectively reducing false thermal anomalies and enhancing the precision of geothermal zone identification, this integrated approach improves the applicability of remote sensing techniques for geothermal exploration. Furthermore, it provides a robust framework for assessing sustainable energy resources in regions with complex terrain.