Space-Based Remote Sensing Inversion Model for Key Soil Parameters in the Study Area

The model is based on the External Parameter Orthogonalization (EPO) algorithm and utilizes measured soil and crop residue (straw) spectral data to simulate mixed spectral datasets under different moisture gradients and coverage conditions. Through principal component analysis (PCA), it separates and removes spectral variations caused by moisture changes, thereby correcting water-interference signals in soil spectra.

The core inputs of the model are pure soil spectra and pure straw spectra, and the output is a pure soil spectral dataset under different moisture gradients after EPO correction. This dataset supports the construction of space-based remote sensing inversion models for key soil parameters (SOM, TN, Clay, MC, TSS, etc.).