Improved PROSPECT Model Based on Optimization of the Internal Blade Structure and Absorption Coefficient

Radiation transfer is an important physical basis for establishing the relationship between spectral and biochemical information. In this article,the interior of the blade is regarded as superimposed by layers with different optical characteristics. The PIOSL (PROSPECT consider the internal optical structure of the leaves) model was proposed, and the element- specific absorption coefficients in the two-layer structure of the leaves in the PIOSL-2 model (two layers of PIOSL) were optimized. By inputting the structural parameters of the two layers and the chlorophyll, water, and dry matter content in each layer, the absorption coefficients of the two layers were optimized using Non-dominated sorting genetic algorithm III extreme learning machine (NSGA-III).Assuming that the specific absorption coefficients of carotenoids and anthocyanins would be included in the chlorophyll. The reflectance spectra of four open data sets are simulated by using the new specific absorption coefficient curves, and their RMSE is calculated and compared with the RMSE of PIOSL-2 and PROSPECT models before absorption coefficient optimization.There were strong absorption peaks at 1400, 2000, and 2400 nm in the second layer of leaves, while the absorption characteristics of chlorophyll, water, and dry matter in the first layer were consistent with those of PROSPECT. The PIOSL-2 model for optimized absorption coefficient accurately simulated the reflectivity of two layers with different optical characteristics, and the mean RMSE of reflectance in the four datasets were 0.0248, 0.0190, 0.0111, and 0.0564. The idea of hierarchical optimization of the components absorption coefficients of leaves is feasible, and the PIOSL-2 model optimized using the NSGA-III can better explain the response principle of leaf biochemical parameters to the leaf spectrum.