Evapotranspiration (ET) is a key parameter in climatological and hydrological models. Moreover, the knowledge of ET at a local scale in agricultural areas may improve the irrigation practices. An operative method using remote sensing techniques would provide spatial and temporal continuous ET data. However, there are limitations in remote sensing data, especially due to the spatial and temporal resolution of the images. For agricultural practices, high spatial and temporal resolution is desired, but nowadays no sensor offers both. The Sentinel-2 sensor has a 5-day revisit cycle and 10-30 m spatial resolution in the visible and near infrared (VNIR) bands. However, no thermal band (TIR) is available, which is the key input in the models for ET estimation based on the surface energy balance. A simple disaggregation procedure is applied in this work to MODIS-Spot images to derive TIR data at 10 m spatial resolution. The disaggregated temperatures are further used as inputs in the STSEB approach (Simplified Two Source Energy Balance) to estimate surface energy fluxes. Ground data in a vineyard and a grass field were used for validation. Average errors of 6%, 21% and 20% were obtained for net radiation, sensible heat flux and evapotranspiration, respectively.