A geographically weighted regression-based soil moisture product using cygnss gnss-r data

The use of the Cyclone Global Navigation Satellite System (CYGNSS) for soil moisture (SM) estimation is of interest. However, the advantage of the variable resolution of CYGNSS was not fully utilized, leading to the loss of detailed information. Geographically Weighted Regression (GWR) permits the co-existence of diverse spatial relationships across different geographic regions, with the regression coefficient varying spatially rather than being globally constant, thus enabling coefficient adjustments within specific spatial boundaries. Advanced GWR-based SM estimation offers a signif icant improvement over other competing estimation models. This study demonstrated that the CYGNSS with high temporal and spatial resolution has the potential for high-resolution independent SM retrieval.