Identification of geothermal anomalies from Landsat derived land surface temperature, Mount Meager volcanic complex, British Columbia, Canada

Abstract

Land surface temperature (LST) from satellite images contains meaningful signatures of geothermal heat flux (GHF) for geothermal exploration. However, the signal is mixed with solar radiation dominated features, making it difficult to identify GHF anomaly. Here we propose a novel method to tackle this problem that removes the time variant solar component based on principles of energy balance. Through an iteration process examining multiple LST maps from different seasons, the temporally invariant GHF component can be revealed. We tested this method by examining the Mount Meager Volcanic Complex area in British Columbia, Canada where data of known geothermal prospects are publicly accessible for validation. Seventy-two Landsat-8 cloud-free LST maps acquired in the last 10 years, were employed to extract the GHF component. Four high GHF anomalies are identified and two are consistent with areas of known hot spring swarms that occur above identified geothermal prospects. A third anomaly is spatially coincident with an active landslide site where warm seeps from the sliding surface and faults/fractures within the moving land mass are responsible for the anomalies. The anomalies in the fourth one are predominately anthropogenic, related to heat emission from hydropower facilities. The proposed method provides an efficient way to extract non-solar sourced LST anomalies, adding a cost-effective tool for geothermal exploration, and environmental/geohazard monitoring.