Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment

Abstract

To meet the demand for intelligent measurements of canopy morphological parameters, a mobile LiDAR scanning system with LiDAR and IMU as the main sensors was constructed. The system uses a LiDAR-IMU tight coupling odometry method to reconstruct a point cloud map of the area surveyed. After using the RANSAC algorithm to remove the map ground, the European clustering algorithm is used for point cloud segmentation. Finally, morphological parameters of the canopy, such as crown height, crown diameter, and crown volume, are extracted using statistical and voxel methods. To verify the algorithm, a total of 43 trees in multiple plots of the campus were tested and compared. The algorithm defined in this study was evaluated with manual measurements as reference, and the morphological parameters of the canopy obtained using the LOAM and LeGO-LOAM algorithms as the basic framework were compared. Experiments show that this method can be used to easily obtain the crown height, crown diameter, and crown volume of the area; the correlation coefficients of these parameters were 0.91, 0.87, and 0.83, respectively. Compared with the LOAM and LeGO-LOAM methods, they were increased by 0.004, 0.12, and 0.13 and 0.07, 0.15, and 0.04, respectively. The test results for this new system are positive and meet the requirements of horticulture and orchard measurements, indicating that it will have significant value as an application.