Validation of high-resolution surface soil moisture time series retrieved by means of SAR interferometry

This paper presents a novel algorithm for high-resolution soil moisture retrieval based on Synthetic Aperture Radar (SAR) interferometry and closure phases. The proposed method efficiently processes long SAR time series with minimal computational cost, generating a soil moisture measurement for each acquisition. Soil moisture data were derived from Sentinel-1 SAR imagery and validated across seven different test sites. Retrieval results were compared with modeled soil moisture data from land surface models, alternative remote-sensing products, and in situ measurements. The algorithm demonstrates strong correlations with modeled soil moisture, particularly in areas characterized by high interferometric coherence. However, performance was expectedly limited in regions with low interferometric coherence due to factors such as vegetation cover or snow cover. Looking ahead, this study identifies some relevant directions for future research, including the integration of backscatter information alongside phase data and the adaptation of the algorithm for SAR missions operating at different frequencies (e.g., L-band) or with very dense acquisition schedules (e.g., geosynchronous platforms). These advancements would further enhance the applicability and accuracy of soil moisture retrieval using SAR-based techniques.