Estimating clumping index of woody canopy with terrestrial lidar data

The terrestrial LiDAR technology can provide canopy structural information implicitly contained within point clouds data and it is a popular tool, particularly in forestry applications. Clumping index characterizes the spatial distribution of the canopy and quantifies the degree of the real distribution deviate from the random case. In this paper, a new method was proposed to estimate the clumping index with terrestrial LiDAR data. The canopy clumping index of each zenith angle was estimated by the logarithmic gap averaging method after establishing voxel-based model, Conversing coordinate system and calculating the gap fraction. In addition, the digital hemispherical photographs (DHP) technology was used for verifying the effectiveness of the proposed approach. The results showed that the correlation coefficient R-2 between DHP and LiDAR is 0.62 when the voxel size is 0.2m*0.2m*0.2m. For a certain zenith angle, the smaller the voxel size is, the larger the clumping index is, and the converse is also true.