Changes in Land Use/Land Cover (LULC) generate several impacts which affect the energy balance of the Earth and, consequently, modifying the climate of a region. Accordingly, one of the most important indicators of this modification is the Land Surface Temperature (LST). The present work aims to analyze the relationship between LULC and LST, determining the influence of LULC on LST using Geographical Information Systems (GIS) and Remote Sensing (RS) techniques. The selected study area was the San Luis Potosí Basin, México (SLPB). A temporal analysis has been developed for 2007 and 2020. Satellite images from Landsat 5 TM and 8 OLI/TIRS has been used to calculate LST through a single-channel algorithm for winter and spring. LULC has been determined from a supervised classification with neural network algorithm. Finally, change rates for LULC and LST were assessed. The results indicate that an LST increase of 11 °C from 2007 to 2020 has been detected in the region. Also, results showed that covers with spare vegetation or without vegetation have the highest temperatures (29°C to 32°C). In comparison, the covers with dense vegetation and water showed the lowest temperatures (23°C to 25°C). This type of research allows addressing the LULC effects on LST, as well as prove its importance in improving land use planning systems.