Retrieving 2-D Leaf Angle Distributions for Deciduous Trees From Terrestrial Laser Scanner Data

Terrestrial laser scanning is a promising tool for estimating leaf angle (including leaf inclination and azimuthal angles) distribution (LAD). However, previous studies focus on the retrieval of leaf inclination angle distribution, very few studies have considered the distribution of leaf azimuthal angle due to the restriction of measurement techniques. In this paper, we developed a new method to obtain more accurate leaf inclination and azimuthal angle estimations based on leaf point cloud segmentation and filtration and then fit LAD functions using two-parameter Beta-distribution model. In addition, we constructed a new projection coefficient model with two parameters G(theta, phi) using Nilson's algorithm based on the accurate retrieval of LAD. To assess the influence of leaf numbers on leaf inclination and azimuthal angle estimations, we modeled 160 individual leaves and 10 trees with different leaf numbers. In addition, to validate the final results, we also sampled three magnolia trees with different leaf numbers and manually measured leaf inclination and azimuthal angles of all their leaves using an angle measurement device. All results showed that the method proposed in this paper can provide accurate leaf inclination and azimuthal angles (leaf inclination angle: R-2 = 0.98, RMSE = 2.41 degrees and leaf azimuthal angle: R-2 = 0.99, RMSE = 3.44 degrees). The simulated LAD and G(theta, phi) estimations based on these leaf inclination and azimuthal angles were strongly correlated with those obtained from ground truth measurements (P > 0.05)