Agradecimentos: We acknowledge the constructive comments by Tahmasb Hatami (Department of Chemical Engineering, UNICAMP), Morteza Sadeghi (California Department of Water Resources), and Zhenzhong Zeng (Princeton University) during the thermal, hydrological, and evaporation modeling, respectively. We are thankful to NASA’s ASTER User Authorization Committee for enabling us to order new ASTER data and Zhang Xia (Chinese Academy of Science) for providing the dataset used in our first numerical experimentation. This work was financially supported by the Sao Paulo Research Foundation (FAPESP) under grant number 2017/25002-7 and the Brazilian National Council for Scientific and Technological Development (CNPq) grants #437337/2018-9 and #309767/2022-9 Ver menos

Abstract: A physically-based image processing approach, based on a single-source surface energy balance framework, is developed here to model the land surface temperature (LST) over complex/rugged geologic terrains at medium to high spatial resolution (<102 m). This approach combines atmospheric parameters with a bulk-layer soil model and remote-sensing-based parameterization schemes to simulate surface temperature over bare surfaces. The model’s inputs comprise a digital elevation model, surface temperature data, and a set of land surface parameters including albedo, emissivity, roughness length, thermal conductivity, soil porosity, and soil moisture content, which are adjusted for elevation, solar time, and moisture contents when necessary. High-quality weather data were acquired from a nearby weather station. By solving the energy balance, heat, and water flow equations per pixel and subsequently integrating the surface and subsurface energy fluxes over time, a model-simulated temperature map/dataset is generated. The resulting map can then be contrasted with concurrent remote sensing LST (typically nighttime) data aiming to remove the diurnal effects and constrain the contribution of the subsurface heating component. The model’s performance and sensitivity were assessed across two distinct test sites in China and Iran, using point-scale observational data and regional-scale ASTER imagery, respectively. The model, known as the Surface Kinetic Temperature Simulator (SkinTES), has direct applications in resource exploration and geological studies in arid to semi-arid regions of the world Ver menos