Estimation of High-Resolution Soil Moisture from Dual Frequency Synthetic Aperture Radar (SAOCOM L-Band & Sentinel-1 C-Band) dataset in the Petacciato landslide area, Italy

Soil moisture estimation can enhance our understanding of preparedness for natural hazards such as landslides, sinkholes, and subsidence. Single-dual polarimetric data are widely used for assessing and monitoring soil moisture due to the availability of the dataset. This research proposes a synergized approach using the change detection method on the dual frequency (SAOCOM L-band and Sentinel-1 C-band) and dual polarimetric (VV-VH) datasets to estimate high spatial-temporal volumetric soil moisture. We present a case study of the Petacciato landslide in Italy. The Petacciato landslide is a coastal area in Europe highly prone to mass movements. Moreover, SAR-derived soil moisture was validated with the meteorological dataset.