Abstract
Mobile laser scanning (MLS) is widely used in the mapping of forest environments. It has become important for extracting the parameters of forest trees using the generated environmental map. In this study, a three-dimensional point cloud map of a forest area was generated by using the Velodyne VLP-16 LiDAR system, so as to extract the diameter at breast height (DBH) of individual trees. The Velodyne VLP-16 LiDAR system and inertial measurement units (IMU) were used to construct a mobile measurement platform for generating 3D point cloud maps for forest areas. The 3D point cloud map in the forest area was processed offline, and the ground point cloud was removed by the random sample consensus (RANSAC) algorithm. The trees in the experimental area were segmented by the European clustering algorithm, and the DBH component of the tree point cloud was extracted and projected onto a 2D plane, fitting the DBH of the trees using the RANSAC algorithm in the plane. A three-dimensional point cloud map of 71 trees was generated in the experimental area, and estimated the DBH. The mean and variance of the absolute error were 0.43 cm and 0.50, respectively. The relative error of the whole was 2.27%, the corresponding variance was 15.09, and the root mean square error (RMSE) was 0.70 cm. The experimental results were good and met the requirements of forestry mapping, and the application value and significance were presented.
Highlights
With the development of light detection and ranging (LiDAR) technology, researchers in various fields began to apply it for modelling analysis
Point cloud map in the forest area was processed offline, and the ground point cloud was removed by the random sample consensus (RANSAC) algorithm
The stem mapping accuracy was 87.5%, and the root mean square errors (RMSEs) of the estimates of the diameter at breast height and the location were 2.36 cm and 0.28 m, respectively. These results indicated that the Mobile laser scanning (MLS) system has the potential to accurately map large forest plots, and further research on mapping accuracy and cost–benefit analyses is needed
Summary
With the development of light detection and ranging (LiDAR) technology, researchers in various fields began to apply it for modelling analysis. In the field of aerospace assembly, horizontal docking assembly is a fundamental process. Zhang et al [1] segmented the point cloud of the cylindrical parts obtained by a 3D laser scanner into a series of parallel planar profiles, and ellipse fitting was employed in order to estimate each center of the section profile. The pose of the whole part can be obtained through a spatial straight line fitting with these profile centers. M-estimation and RANSAC was developed, avoiding the influence of the interference features on the surface of the parts in the practical assembly process. Pawel Burdziakowski [2] merged laser scanning data and images together using the iterative closest point (ICP), and the structure-from-motion (SfM)
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