Groundwater temperatures (GWTs) vary based on the local geothermal heat flux, the energy budget at the surface, and land cover. With subsurface temperature data being scarce, standard techniques for the spatial interpolation often produce unrealistic representation of shallow GWT. It has been shown that utilizing remote sensing data can reproduce shallow GWT at an error of roughly 1 K. In our contribution, we apply such a technique to the state of Saxony-Anhalt, Germany. The estimation is trained and validated with a set of over 600 observation wells. The data used comprises data from the Landesbetrieb für Hochwasserschutz und Wasserwirtschaft Sachsen-Anhalt (LHW) as well as own monitoring campaigns for the cities of Magdeburg, Halle (Saale), and Dessau. Together with different satellite datasets, such as land surface temperature and building density, we use this measured GWT data to derive spatially resolved estimated GWTs (eGWT) for Saxony-Anhalt. The measured and estimated GWTs are then correlated to the land cover at the location. Thus, this study aims to (1) present measured GWT and eGWT distribution for Saxony-Anhalt, (2) assess the application of satellite data for estimating shallow GWT, and (3) research the correlation between GWT/eGWT and land cover.