Soil Moisture Retrieval Using Gnss-R Data

The aim of this study is to propose an inversion algorithm for CYGNSS constellation data, which can be used for the monitoring of soil moisture. A change detection approach based on a 21-month CYGNSS data time series is proposed, and is processed to retrieve daily average reflectivity over a grid with a spatial resolution equal to $0.5 ^{\circ} \mathrm{x}0.5 ^{\circ}$. Auxiliary data, including PROBA-V optical measurements and SRTM Digital Terrain Model products are used to account for the influence of vegetation and relief. The proposed estimates are validated at three different African sites (Merguellil, Tunisia; Basso Dallo, Niger; and Ouémé, Benin), using field moisture measurements acquired at 5 cm soil depth.