Physics-Based Retrieval of Surface Roughness Parameters for Bare Soils from Combined Active-Passive Microwave Signatures

In the past the effect of soil roughness was often considered secondary within the determination of soil moisture from remote sensing data. Several studies showed that accurate determination of soil roughness leads to an improved estimation of soil moisture. Two standard parameters in microwave sensing to describe the surface roughness are the standard deviation of the surface height variation $s$ and the surface correlation length $l$ with its corresponding autocorrelation function (ACF). Both parameters (s, l) affect the emissivity measured by radiometers as well as the backscattering observed by radars. In this study, we develop a physics-based approach to retrieve $s$ and $l$ by combining both microwave signals based on active-passive microwave covariation. To test the approach, containing a forward model and a retrieval algorithm, we used active/passive microwave data measured with the ComRAD truck-based SMAP simulator at L-band. Results and validations with corresponding field measurements on ground show that $s$ and $l$ can be estimated when using this approach. The physics-based retrieval algorithm works robustly for two investigated test fields having an RMS-Error of 0.68 cm and 0.69 cm between the microwave-based and field-measured s-values, and of 3.13 cm and 3.04 cm for l-values. Validation of the results reveals that the influence of the ACF, needed within the retrieval, is distinct.