The feasibility of soil moisture retrieval from C-band Sentinel-1 data has been widely acknowledged, with pre-operational 1-km products currently available at regional and/or continental scale using the long-term (LTCD) or short-term change detection (STCD) methods. Both algorithms share the same assumptions of time-invariant roughness and vegetation, which can be questionable even for a short period of 4 Sentinel-1 acquisitions (18–36 days). An advanced change detection (ACD) method is proposed in this study for an improved soil moisture retrieval from Sentinel-1 data, including two main modifications with respect to the existing STCD methods: i) approximating the effect of temporal varying vegetation on the Sentinel-1 backscatter as a variation in the two-way attenuation, and ii) a temporal soil moisture constraint based on the coarse Soil Moisture Active Passive (SMAP) soil moisture product to partly remove the uncertainty caused by vegetation and/or roughness changes. The evaluation, based on time-series observations from 34 OzNet stations and ground samples collected during the Fifth Soil Moisture Active and Passive Experiment (SMAPEx-5) showed that the ACD improved the correlation coefficient (R), root mean square error (RMSE) and un biased RMSE (ubRMSE), achieving 0.66, 0.071 m3/m3 and 0.071 m3/m3 at the point scale, 0.77, 0.063 m3/m3 and 0.051 m3/m3 at 1-km scale, 0.80, 0.055 m3/m3 and 0.050 m3/m3 at 3-km scale. The contribution of the two modifications was further investigated using 559 stations from 22 networks across the world, showing that: i) the two modifications can increase R by 0.08–0.13 and reduce the retrieval RMSE by 0.009–0.013 m3/m3 (10% - 15% relative), and ii) the retrieval over densely vegetated areas or areas with large temporal vegetation variation can benefit more from the proposed modifications. The ACD achieved stable performance for various Sentinel-1 orbits/passes and maintained a stable performance for retrieval windows up to 30 Sentinel-1 acquisitions, providing a promising alternative for achieving consistent soil moisture retrievals from Sentinel-1.
- Change detection
- High resolution
- Soil moisture
- Synthetic aperture radar (SAR)