Estimating Backward Scattering using GNSSReflectometry Measurements for Soil Moisture Retrieval

Soil Moisture (SM) is a key geophysical variable that enables a better understanding of theEarth’s hydrological processes. Missions like Soil Moisture Ocean Salinity (SMOS) and Soil Moisture ActivePassive (SMAP) have been the primary sources of SM estimations for years. The NASA-ISRO SyntheticAperture Radar (NISAR) mission, planned to launch in 2024, will bring L-band and S-band SARmeasurements that will be used for SM estimation. Consequently, investigations to link SMAP with NISARto produce accurate SM retrievals at improved spatial resolutions will be a focus to many research initiatives.This investigation aims to set the basis to use polarimetric Global Navigation Satellite System-Reflectometry(GNSS-R) products to enhance the temporal resolution of NISAR’s L-band SAR data through its typical 12-day period. As a proof of concept, we model SMAP radar backscatter measurements from SMAPReflectometry(SMAP-R) measurements, using the 3 months of data collected by the SMAP radar while itwas operational. The model is based on the sensitivity of polarimetric GNSS-R to roughness, vegetation, andSM, as well as on the complementary sensitivity existing between forward and backward scatter. Differentregression models are implemented using single-, dual-, and full-polarization GNSS-R measurementssynthetized from SMAP-R data. This study highlights the importance of the new constellations ofpolarimetric GNSS-R being built and shows how those frequent measurements can serve L-band SARmissions to improve their time resolution.