Soil moisture plays an important role in understanding climate change and hydrology, and L-band passive microwave radiometers have been verified as effective tools for monitoring soil moisture. This paper proposes a novel, simplified algorithm for bare surface soil moisture retrieval using L-band radiometer. The algorithm consists of two sub-algorithms: a surface emission model and a soil moisture retrieval model. In analyses of the advanced integral equation model (AIEM) simulated database, the surface emission model was developed to diminish the effects of surface roughness using dual-polarization surface reflectivity. The soil moisture retrieval model, which was calibrated using the Dobson simulated database, is based on the relationship between the adjusted real refractive index
and the volumetric soil moisture. Soil moisture can be determined via a numerical solution that uses several freely available input parameters: dual-polarization microwave brightness temperature, surface temperature, and the contents of sand and clay. The results showed good agreement with the input soil moisture values simulated by the AIEM model, with root mean square errors (RMSEs) lower than 3% at all incidence angles. The algorithm was then verified based on data from the four-year L-band experiments conducted at Beltsville Agricultural Research Center (BARC) test sites, achieving RMSEs of 4.3% and 3.4% at 40° and 50°, respectively. These results indicate that the simplified algorithm proposed in this paper shows a very good accuracy in soil moisture retrieval. Additionally, the algorithm exhibits a better performance for the large incidence angle radiometers in L-band such as those produced by the Soil Moisture Active and Passive (SMAP).
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