Sentinel-1 soil moisture at 1 km resolution: a validation study

This study presents an assessment of a pre-operational soil moisture product at 1 km resolution derived from satellite data acquired by the European Radar Observatory Sentinel-1 (S-1), representing first space component Copernicus program. The consists estimate surface volumetric water content Θ [m3/m3] and its uncertainty [m3/m3], both km. retrieval algorithm relies on time series based Short Term Change Detection (STCD) approach, taking advantage frequent revisit S-1 constellation that performs C-band Synthetic Aperture (SAR) imaging. performance is estimated through direct comparison between 1068 images against in situ measurements 167 ground stations located Europe, America Australia, over 4 years January 2015 December 2020, depending site. paper develops method to spatial representativeness error (SRE) arises mismatch retrieved point-scale observations. impact SRE standard validation metrics, i.e., root mean square (RMSE), Pearson correlation (R) linear regression, quantified experimentally assessed using collected dense hydrologic network (4 − 5 stations/km2) Apulian Tavoliere (Southern Italy). Results show for hydrological RMSE are ~0.06 m3/m3 0.71, respectively, whereas sparse networks, station/km2, increases ~0.02 (70% Confidence Level). Globally, characterized intrinsic (i.e., with removed) ~0.07 range [0.03, 0.60] R 0.54. A breakdown per dry, medium wet ranges also implications setting realistic requirements SAR-based discussed together recommendations density