Fast and Accurate Simulation of Canopy Reflectance under Wavelength-Dependent Optical Properties Using a Semi-Empirical 3D Radiative Transfer Model

Abstract

Generating canopy-reflectance datasets using radiative transfer models under various leaf and soil optical property combinations is important for remote sensing retrieval of vegetation parameters. One-dimensional radiative transfer models have been frequently used. However, three-dimensional (3D) models usually require detailed 3D information that is difficult to obtain and long model execution time, limiting their use in remote sensing applications. This study aims to address these limitations for practical use of 3D models, proposing a semi-empirical speed-up method for canopy-reflectance simulation based on a LargE-Scale remote sensing data and image Simulation model (LESS), called Semi-LESS. The speed-up method is coupled with 3D LESS to describe the dependency of canopy reflectance on the wavelength, leaf, soil, and branch optical properties for a scene with fixed 3D structures and observation/illumination configurations, allowing fast generating accurate reflectance images under various wavelength-dependent optical parameters. The precomputed dataset stores simulated multispectral coefficient images under few predefined soil, branch, and leaf optical properties for each RAdiation transfer Model Intercomparison-V scene, which can then be used alone to compute reflectance images on the fly without the participation of LESS. Semi-LESS has been validated with full 3D radiative-transfer-simulated images, showing very high accuracy (root mean square error < 0.0003). The generation of images using Semi-LESS is much more efficient than full LESS simulations with an acceleration of more than 320 times. This study is a step further to promote 3D radiative transfer models in practical remote sensing applications such as vegetation parameter inversions.