This study aims to explore the combined detection capabilities of spaceborne GNSS-R (Global Navigation Satellite System Reflectometry) and scatterometers for remote sensing applications. Specifically, we focus on the enhancement effect of integrating the two technologies, which differ in their scattering mechanisms and observation modes, on the accuracy of ocean and land surface parameter retrieval. Two experiments were conducted in two typical scenarios: ocean surface wind speed and soil moisture retrieval. GNSS-R, which provides unique forward-scattered signals with high temporal and spatial resolution, and scatterometer, which is an active microwave sensor that receives backward-scattered signals, were compared individually and in combination. The evaluation was based on their operational characteristics, particularly their complementary features, including forward versus backward scattering and active versus passive observation modes. The results show significant improvements when combining the two technologies. In near-real-time applications, the combination reduced the Root Mean Square Error (RMSE) of sea surface wind speed retrieval by at least 13% compared with single-source sensors. In large-scale applications, the high-precision benefits of the combination extended to a broader coverage area, which reduced the RMSE for soil moisture retrieval by at least 6%. This study demonstrates that integrating spaceborne GNSS-R and scatterometer data can substantially improve the accuracy of remote sensing measurements, specifically in near-real-time and large-scale scenarios. Future research should further optimize observation geometry, polarization combinations, and band selections to enhance retrieval methods for ocean and land surface parameters.

spaceborne GNSS-R;scatterometer;forward scattering;backward scattering;combined retrieval;ocean surface wind speed;soil moisture;DDM;reflectivity;NRCS