Exploring the Potential of UAV LiDAR Data for Trunk Point Extraction and Direct DBH Measurement

Abstract

The accurate measurement of diameter at breast height (DBH) is one of the essential tasks for biomass estimation at an individual tree scale. This paper aims to explore the potential of unmanned aerial vehicle (UAV) based light detection and ranging (LiDAR) for trunk point extraction and direct DBH measurement. First, the trunk point cloud for each tree is extracted based on UAV LiDAR data by the multiscale cylindrical detection method. Then, the DBH is directly measured from the point cloud via the multiscale ring fitting. Lastly, we analyze the influence of scanning angle and mode on trunk point extraction and DBH measurement. The results show that the proposed method can obtain high accuracy of trunk point extraction and DBH measurement with real (R2 = 0.708) and simulated (R2 = 0.882) UAV LiDAR data. It proves that the UAV LiDAR data is feasible to directly measure the DBH. The highest accuracy was obtained with the scanning angles ranging from 50 to 65 degrees. Additionally, as the number of routes increases, the accuracy increases. This paper demonstrates that the UAV LiDAR can be used to directly measure the DBH, providing the scientific guidance for UAV path planning and LiDAR scanning design.

Keywords

• UAV LiDAR
• DBH
• trunk point cloud
• scanning angle
• scanning mode