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