A new approach for calculating mesoscale soil moisture maps from coarse resolution (500 m - 1 km) SAR data utilizing spatially reduced ERS data is presented. The processing of the radar data is described which includes a correction for the impact of surface roughness, plant water content and soil texture upon of the backscatter intensity. First, the portion of the pixel which does not provide soil moisture information (forest, built-up areas, water) is corrected, then the corrected backscatter intensity is normalized to a reference landuse (cereals). The required landuse map was derived from LANDSAT data. However, these landuse classes which must be distinguished to account for differences in surface roughness and plant water content, may also be derived from AVHRR spectro-temporal unmixing. Using model results and measurements together with the landuse map, the impact of the plant water content was corrected. Finally, the soil texture was taken into account to calculate the mesoscale surface soil moisture. The resulting soil moisture was validated quantitatively using ground truth measurements. A qualitative validation of the spatial patterns was carried out through by comparison of the calculated soil moisture with precipitation patterns. A good agreement was found between ground based and satellite derived soil moisture (RMSQ less than 5 VOL%).