Sub-Pixel-Level Backscattering Contributions Decomposition and Estimation Based on Spectral Unmixing Techniques

The complexity of land types and the limited spatial resolution of Synthetic Aperture Radar (SAR) imagery have led to the widespread presence of mixed pixels in radar backscatter images. The signal mixture of Endmembers within mixed pixels hinders the establishment of accurate relationships between pure Endmember’s parameters and the corresponding backscatter coefficient, thereby significantly reducing the accuracy of surface parameter inversion. However, few studies focused on decomposing and estimating the pure backscatter signals within mixed pixels. This paper proposes a novel approach based on hyperspectral unmixing techniques and the microwave backscatter contribution decomposition model to estimate the pure backscatter coefficients of all Endmembers within mixed pixels. Experimental results demonstrate that the proposed method can relatively accurately estimate the backscatter coefficients of all end members of mixed pixels. For mixed pixels composed of grassland and soil in the test area, the proportion of pixels with a relative error within 20% in estimating soil and grass endmember backscattering coefficients was close to 80% of the total number of tested pixels. Furthermore, the spatial distribution of the estimated Endmember backscattering coefficients exhibited a high degree of consistency with the endmember types, structures, and conditions that influence their backscattering behavior.