LAI Retrieval Using PROSAIL Model and Optimal Angle Combination of Multi-Angular Data in Wheat

Abstract

Leaf area index (LAI) is a crucial parameter of vegetation structure in ecosystem, climate, and crop yield models. The radiative transfer model (RTM) inversion method is useful for estimating LAI, due to its well-founded physical basis and independence of vegetation types. Multi-angular observations can provide more structure information of vegetation, and therefore the RTM inversion incorporating with multi-angular data may have the potential to estimate LAI much more accurately. In this paper, the performances of LAI retrieval with several angle combinations were explored using the PROSAIL model and multi-angular data based on a lookup table (LUT) method. A high accuracy (R2=0.9371 and RMSE=0.8914 ) was obtained with the optimal angle combination (-20°,-10°,0°,10°) . Results demonstrated that the near-nadir angle and the back-scattering angles in the NIR band had the better capabilities on LAI estimation, so it was necessary to determine the optimal angle combination when dealing with the multi-angular data. It provided the opportunity to improve the retrieval accuracy of LAI and some help to the angle set of the new multi-angle remote sensing sensors.