STUDY ON THE EXPLAINABLE ABILITY BY USING AIRBORNE LIDAR IN STAND VALUE AND STAND COMPETITION

Abstract

Forest canopy structure is composed by the various species. Sun light is a main factor to affect the crown structures after tree competition. However, thinning operation is an appropriate way to control canopy density, which can adjust the competition conditions in the different crown structures. Recently, Airborne Light Detection and Ranging (LiDAR), has been established as a standard technology for high precision three dimensional forest data acquisition; it could get stand characteristics with three-dimensional information that had develop potential for the structure characteristics of forest canopy. The 65 years old, different planting density of Cryptomeria japonica experiment area was selected for this study in Nanytou, Taiwan. Use the LiDAR image to estimate LiDAR characteristic values by constructed CHM, voxel-based LiDAR, mu0ltiple echoes, and assess the accuracy of stand characteristics with intensity values and field data. The competition index was calculated with field data, and estimate competition index of LiDAR via multiple linear regression. The results showed that the highest accuracy with stand characteristics was stand high which estimate by LiDAR, its average accuracy of 91.03%. LiDAR raster grid size was 20 m × 20 m for the correlation was the best, however, the higher canopy density will reduce the accuracy of the LiDAR characteristic values to estimate the stand characteristics. The significantly affect canopy thickness and the degree of competition in different planting distances.