Application of remote sensing techniques to geothermal exploration at geothermal fields in the United Arab Emirates

Satellite thermal infrared remote sensing is an important technique for exploring and monitoring thermal properties of hot spring regions. We used Landsat 8 Optical Land Imager (OLI)–Thermal Infrared Scanner (TIR) sensor images to observe the thermal status of three hot spring areas in the United Arab Emirates for the first time in 2017. Landsat 8 TIR band 10 images were used to estimate land surface temperatures (LST) using a mono-window algorithm, emissivity using a normalized difference vegetation index (NDVI) threshold method, and radiative heat fluxes (RHF) and heat discharge rates (HDR) using the Stefan–Boltzmann law and a relationship coefficient. The highest maximum LST were about 43°C, 40°C, and 27°C at the Ain Al Faidha (AF), Green Mubazzarah (GM), and the Ain Khatt (AK) hot spring areas, respectively. The LST were about 13°C, 10°C, and 4°C above the pixel (30 m × 30 m) average ambient temperatures, although point LSTs might be higher than these. The highest RHF were 68, 83, and 21 W/m2, and total radiative heat losses approximately 157, 530, and 15 MW, at GM, AF, and AK, respectively. Total HDR were estimated to be 1013, 3423, and 94 MW for GM, AF, and AK, respectively, using a relationship coefficient between HDR and RHF of 6.49. The LST and RHF increased with decreasing NDVI value, i.e., bare or desert surface showed higher values than vegetated surface. This study indicates that satellite remote sensing is a cost-effective and efficient method for assessing the thermal components of hot springs.