Regularization-Based Retrieval Method for Surface Reflective Property Parameters

Climate studies at regional and global scales, require accurate descriptions of the light reflecting behaviors of the underlying surfaces at atmospheric boundary layers. A regularized constraint retrieval method is correspondingly proposed for this purpose. The key to the presented method is the determination of the regularization parameter (RP). In order to stabilize the quantitative retrievals of land surface reflective property (SRP) parameters, the optimized RP is obtained via the corner point of the L-curve. Numerical retrieval tests in Beijing-Tianjin-Tangshan region and entropy reduction results suggest that information indices in visible-red and near-infrared channels reach 11.682 2 and 10.072 6; and that the average information indices in these two channels, before and after SRP retrie-vals using L-curve-based regularization (RLC) method, are 0.440 0 and 0.354 6, with the greatest increase reaching 2.467 2 and 2.290 5, respectively. The advantage of the RLC method lies in the independence of the a priori surface parameters knowledge. The RLC method is very effective and useful for the retrievals of surface parameters in the cases of insufficient satellite observations.