VBRT: A novel voxel-based radiative transfer model for heterogeneous three-dimensional forest scenes

Abstract

Modeling the radiative transfer (RT) in heterogeneous forest scenes is important for understanding biophysical processes, as well as retrieving information from remotely sensed data. LiDAR (Light Detection and Ranging) is capable of providing highly detailed three-dimensional (3D) canopy structural information that can be used to parameterize RT models. In previous studies, point cloud data (such as terrestrial LiDAR data) are often voxelized with coarse resolutions, and the foliage voxels are often assumed to be turbid medium. In this study we propose a new voxel-based RT model, namely VBRT, that uses high resolution solid voxels to approximate 3D structure of forest more accurately than coarse resolution turbid medium voxels used in previous studies. Parallel computing techniques are used to speed up computation and the model can run on high performance computing (HPC) platforms. VBRT was tested in four virtual forest scenes, using the well-known physically based ray tracer (PBRT) as a benchmark. The Discrete Anisotropic Radiative Transfer (DART) model, which is based on turbid medium voxels, was also compared. Experimental results show that simulated digital imagery and bi-directional reflectance factor (BRF) by VBRT and PBRT are in good agreement, and the difference in simulation results can be reduced by using higher resolution voxels or larger number of samples per pixel. According to our test, parameterizing VBRT using high resolution terrestrial LiDAR data with 0.02m voxels can produce more accurate results than DART with turbid medium voxels (0.1m), although VBRT is more computation-intensive due to the use of higher resolution voxels. Our results indicate that VBRT has good potential in modeling radiation transfer in forests, as it is possible to parameterize the model using high density point cloud data such as terrestrial LiDAR data.