Impact of Right-Hand Polarized Signals in GNSS-R Water Detection Algorithms

The water detection algorithm for the dual-polarized HydroGNSS mission was validated using spaceborne left-hand circular polarization (LHCP) data from the cyclone global navigation satellite system. With the public availability of dual-polarization data from Rongowai, an airborne global navigation satellite system-reflectometry mission, a unique opportunity arises to evaluate the contribution of right-hand circular polarization (RHCP) data to surface water detection. This analysis can offer a deeper understanding of RHCP data and yield predictive insights prior to the HydroGNSS launch. In this study, we initially analyzed coherence indicators in incoherently averaged dual-polarized signals, and subsequently, applied these indicators to a random forest classifier, similar to the HydroGNSS surface inundation algorithm. The findings have been compared with existing flooding products, showing promising results with over 91% agreement in water detection. The analysis revealed that, while the LHCP data exhibit a higher sensitivity to water, the incorporation of the RHCP data enhances the robustness and reliability of the classification. This reinforces the hypothesis that HydroGNSS, operating at dual polarization, might produce a more effective surface water detection product than single-polarization GNSS-R missions.