研究目的
To investigate the potential for linking the PROSAIL physical model with the kernel-driven Ross-Li models for retrieving canopy biophysical/structural variables from satellite multiangle observations.
研究成果
The models show good overall consistency in BRFs and albedos, with potential for linking to retrieve vegetation parameters from satellite BRDF data. However, caution is needed for extreme cases like erectophile vegetation and large view angles.
研究不足
Discrepancies occur at large view zenith angles and for erectophile canopies (large ALA values). The PROSAIL model assumes random leaf azimuth distribution, which may not capture all real-world heterogeneity. Kernel-driven models have predetermined BRDF shapes that may not fit all canopy types perfectly.
1:Experimental Design and Method Selection:
The study uses a simulation-based approach where 20,000 sets of BRFs are generated by the PROSAIL model covering various vegetation parameters. These are input into kernel-driven models (RTCLSR and RTCLTR) for BRF and albedo retrieval. Field measurements from 21 datasets are also used for validation.
2:Sample Selection and Data Sources:
Simulated data from PROSAIL with uniform sampling of parameters; field data from PARABOLA radiometer and other sources covering forest, grass, and crop types.
3:List of Experimental Equipment and Materials:
PROSAIL model code, kernel-driven model algorithms, MODIS BRDF products, field radiometers (e.g., PARABOLA).
4:Experimental Procedures and Operational Workflow:
Generate BRFs with PROSAIL, fit with kernel-driven models using least squares, compare BRFs and albedos using RMSE and bias metrics.
5:Data Analysis Methods:
Statistical analysis including RMSE, bias, R-squared, and sensitivity analysis using trend lines and histograms.
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