Sentinel-1 data sensitivity for soil moisture estimation and its application for in-season monitoring of small land holding farmer plots

The study of soil moisture is crucial for understanding the hydrological cycle and its impact on energy and water exchanges at the land-atmosphere interface. Synthetic Aperture Radar (SAR) data, such as Sentinel-1, has shown potential for estimating soil moisture at high spatio-temporal resolutions. However, the sensitivity of SAR responses to soil moisture and the applicability of Sentinel-1 data for soil moisture estimation at different land covers require further investigation. In this paper, we evaluate the sensitivity of Sentinel-1 data for soil moisture estimation and compare the estimated soil moisture for different land covers. A change detection approach combined with a vegetation scattering model is employed to estimate soil moisture. The results demonstrate that while the change detection approach with vegetation correction improves soil moisture estimation, the accuracy is still not within an acceptable range for plot-level decision-making, such as irrigation management. However, the results show that the soil moisture information obtained from Sentinel-1 data can be suitable for regional-level monitoring applications and decision-making.