Abstract
Effective 3D tree reconstruction based on point clouds from terrestrial Light Detection and Ranging (LiDAR) scans (TLS) has been widely recognized as a critical technology in forestry and ecology modeling. The major advantages of using TLS lie in its rapidly and automatically capturing tree information at millimeter level, providing massive high-density data. In addition, TLS 3D tree reconstruction allows for occlusions and complex structures from the derived point cloud of trees to be obtained. In this paper, an automatic tree skeleton extraction approach based on multi-view slicing is proposed to improve the TLS 3D tree reconstruction, which borrowed the idea from the medical imaging technology of X-ray computed tomography. Firstly, we extracted the precise trunk center and then cut the point cloud of the tree into slices. Next, the skeleton from each slice was generated using the kernel mean shift and principal component analysis algorithms. Accordingly, these isolated skeletons were smoothed and morphologically synthetized. Finally, the validation in point clouds of two trees acquired from multi-view TLS further demonstrated the potential of the proposed framework in efficiently dealing with TLS point cloud data.
Highlights
Three-dimensional (3D) tree modeling strongly supports applications in plant growth simulation, biomass calculation, forest management and protection, and environmental conservation [1,2,3]
This section firstly shows the visual effect of our algorithm based on two datasets of point cloud
Our method generated skeletons of the main structure for both datasets. The results of these two trees demonstrated that our algorithm was able to deal with different shapes and structures, and that the skeletons were basically not affected by the leaves
Summary
Three-dimensional (3D) tree modeling strongly supports applications in plant growth simulation, biomass calculation, forest management and protection, and environmental conservation [1,2,3]. The aforementioned techniques can be conveniently used to build accurate and realistic 3D tree models Among these tools, terrestrial Light Detection and Ranging (LiDAR) scans (TLS) can be well suited for successfully obtaining point clouds of trees in high accuracy and precision in a non-contact non-destructive way, presenting a promising opportunity to construct trees based on the obtained point clouds [4,5,6]. Other earlier tree reconstruction methods need user interaction, for instance, providing branch widths and branching angles, or trees’ general sketches [8]. Such parameters with input data are imported into the tree modeling software to complete the automatic modeling processes [9]
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