A Novel Soil Moisture Retrieval Algorithm for FY-3E GNOS-R Leveraging Multi-Angle Observations

Objective: Develop effective FY-3E GNOS-R algorithm for global soil moisture retrieval.Methods:1.Incorporate first-order vegetation model, consider density, and volume scattering.2.Use multi-angle GNOS-R observations, combine with SMAP data for optimization.3.Tailor algorithm for diverse surface conditions; parameterize surface roughness based on angle.Results: Achieve enhanced retrieval accuracy, RMSE: 0.0235, 0.0264, 0.0191 (g/cm3) for bare, low vegetation, and dense vegetation areas.Limitations: Limited to one month of data; further testing required for broader applicability.Conclusions: GNOS-R proves a robust tool, surpassing previous techniques for global soil moisture estimation.