GNSS-R Soil Moisture Retrieval for Flat Vegetated Surfaces Using a Physics-Based Bistatic Scattering Model and Hybrid Global/Local Optimization

This paper presents a soil moisture retrieval scheme from Cyclone Global Navigation Satellite System (CYGNSS) delay-Doppler maps (DDMs) over land. The proposed inversion method consists of hybrid global and local optimization physics-based bistatic scattering forward model. model was developed for bare-to-densely vegetated terrains, it predicts the circularly polarized radar cross section DDM land surface. tested on both simulated DDMs CYGNSS Soil Moisture Active Passive (SMAP) Yanco core validation site in Australia. About 250 2019 2020 were used validation. grassland forest vegetation types. type grassland. water content (VWC) 0.19 kgm−2 4.89 respectively. For case when surface roughness is known to algorithm, unbiased root mean square error (ubRMSE) estimates less than 0.03 m3m−3 while approximately 0.06 0.09 results 2020, algorithm generally had enhanced performance smaller values moisture. are unknown only single retrieval, showed an expected reduced performance, with ubRMSE 0.12 m3m−3.