Short-term SAR change detection for soil moisture retrieval: A case study over Danish test sites.

This paper investigates the use of a constrained short-term change detection (STCD) method for field-scale soil moisture retrieval from Sentinel-1 synthetic aperture radar (SAR) backscatter. This method estimates changes in surface dielectric properties by analyzing backscatter ratios between consecutive acquisitions, under the assumption that soil moisture fluctuates more rapidly than vegetation and/or roughness changes. The inversion scheme integrates ancillary data, namely a coarse-scale soil moisture product, soil texture maps, and field capacity, to constrain the solution and minimize outliers. The influence of key parameters, including the inversion window size, was examined. Additional corrections are introduced to handle limitations arising from crop type or measurement depth, including a seasonal adjustment model. The approach is validated using in situ soil moisture data from multiple test sites in Denmark. Results show that the STCD method achieves strong agreement with ground-based observations, yielding an overall correlation of R = 0.72, low bias (-0.26%), and an RMSE of 4.32%. These findings support the potential of short-term SAR change detection for scalable, high-resolution soil moisture monitoring in agricultural landscapes where backscatter variability is well characterized.