Land Surface Temperature (LST) is a critical variable in understanding Earth's energy balance, climate patterns, and environmental conditions. LST represents the radiative skin temperature of the land surface, and it plays a crucial role in fields like meteorology, climatology, agriculture, and urban heat studies.

This dataset provides high spatio-temporal resolution LST data, for the four pilot cities involved in CityCLIM (Valencia, Luxembourg, Thesaloniki, Karlsruhe) generated using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model). The ESTARFM method is employed to fuse data from Sentinel-3 and Landsat 8/9 satellites, producing LST data with improved temporal frequency and spatial resolution.

Only scenes that have simultaneous Landsat 8/9 acquisitions are included in this dataset, as these scenes were validated using in situ or other reference data sources. A table with the validation metrics—R², bias, and RMSE (Root Mean Square Error)—is also provided to quantify the accuracy of the generated LST values.

This dataset is valuable for researchers and professionals requiring detailed, validated LST information for environmental monitoring, land management, and climate studies.