Detecting geothermal anomalies using Landsat 8 thermal infrared remotely sensed data

The potential to map geothermal anomalies using remote sensing information has attracted recently much research, reflecting thus the increasing interest for renewable energy resources. Aim of the present work is to highlight areas with geothermal anomalies, as demonstrated by increased Land Surface Temperature (LST) values, that could potentially indicate possible locations for geothermal field development. We hypothesized that an area with increased geothermal potential can possibly have a surface expression through increased LST, that discriminates it from other areas of low geothermal interest. LST is known to be affected by increased heat flow but also from other parameters such as altitude, land cover and meteorological conditions. Therefore, there is need to develop a methodology capable to extract LST signals corresponding to the geothermal component. To delineate areas with constantly higher LST values from surrounding locations, we analyzed Landsat 8 derived LST time series, and accounted for different land cover types and altitudes. To test our hypothesis, we used a well-known geothermal field in Aristino-Alexandroupolis, NE Greece, where it was shown that spatial means of winter LST were significantly greater within geothermal zones. Furthermore, our results indicated that areas within geothermal fields demonstrate winter LST values greater than a certain threshold value for each different land cover type. Therefore, we developed a logical operator algorithm and applied our methodology to Thrace basin - NE Greece. The produced geothermal potential map depicted correctly spot areas, which make part of the known geothermal fields in Eastern Macedonia and Thrace Tertiary sedimentary basins, but also indicated other possible sites with increased potential for future research.