Retrieval of Crop Leaf Area Index from SPOT-5 Data Using a Look-Up-Table Approach
Leaf Area Index (LAI) is a key structural characteristic of vegetation and plays a significant role in global change researches. Aimed at the LAI retrieval from SPOT-5 data, the paper evaluated several Look-Up-Table (LUT) approaches for crop LAI inversion based on PROSAIL model simulation. The experiment results indicate that LUT approach based on model parameter sensitive analysis, selective parameterization is more suitable for crop LAI estimation, with a root mean square error (RMSE) of approximately 0.24 m2/m2 and determination coefficient (R2) of 0.82.