| As an important part of trees,the tree crown undertakes the important function of absorbing carbon dioxide and carrying out photosynthesis.Canopy volume is defined as the size of the space occupied by tree branches and leaves,and is an important geometric quantity for canopy parameters.Due to the different and scattered canopy shapes,the canopy volume factor is often difficult to measure accurately and quickly in large scenes.Based on the point cloud data obtained by the ground and airborne 3D laser scanning systems,this paper focuses on the calculation of the canopy volume.By using the improved α-shape algorithm and the maximum and minimum filtering algorithm respectively,the pedestal method and the Qucik Hull method are implemented.improvement,and the effectiveness of the method is verified by experiments.The main conclusions and research results are as follows:1.Improve the algorithm for calculating tree canopy volume based on the pedestal method.The point cloud sample data of 14 relatively accurate trees were obtained by the ground laser scanner.Based on the original pedestal algorithm,an α-shape boundary extraction method was proposed that considered the point cloud boundary density and dynamically set the αthreshold.The experimental analysis determined the optimal linear iterative step size and layer spacing of the method,and realized the accurate calculation of the canopy volume.2.Improved the algorithm for obtaining canopy volume based on the Qucik Hull algorithm.Aiming at the problem of low calculation efficiency of canopy volume in large scenes,this paper proposes two improved schemes based on 3D spatial index,SMMP(Single direction Maximum and Minimum Point filtering)and MMMP(Multidirectional Maximum and Minimum Point filtering)filtering algorithms,which significantly improve the efficiency of Qucik Hull algorithm to calculate canopy volume,by using the high-precision and high-density canopy point cloud data obtained by laser scanners.and analyze the optimal grid size of the scheme through single-tree experiments.On the premise of ensuring the accuracy,the rapid calculation of the canopy volume is realized.3.Fusion of MMMP filtering algorithm and improved platform algorithm.First,three filtering directions are determined by using the PCA(Principal Component Analysis)algorithm,and then the original point cloud data is filtered by using the MMMP algorithm,the redundant points in the canopy point cloud are eliminated,and the external geometric features of the canopy point cloud are preserved as much as possible.Under the premise,the improved platform algorithm is used to complete the canopy volume calculation while taking into account the calculation efficiency and accuracy.4.Verify the feasibility of the improved algorithm in this paper in large-scale point cloud data.The airborne and ground-based point cloud data of the experimental area were selected,and operations such as data preprocessing,ground point extraction,data normalization based on ground points,single-tree point cloud canopy extraction,and related post-processing were performed respectively.The improved table volume algorithm,the improved Qucik Hull algorithm and the fusion algorithm proposed in this paper are tested,and the results show that the method in this paper has certain practicability in obtaining the canopy volume in large-scale point cloud data. |
