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Tropical Tree Species 3D Modelling and Classification Based on LiDAR Technology

Tropical Tree Species 3D Modelling and Classification Based on LiDAR Technology

Panagiotis Barmpoutis, Tania Stathaki, Jonathan Lloyd, Magna Soelma Bessera de Moura
Copyright: © 2020 |Pages: 22
ISBN13: 9781522552949|ISBN10: 1522552944|ISBN13 Softcover: 9781799829966|EISBN13: 9781522552956
DOI: 10.4018/978-1-5225-5294-9.ch001
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MLA

Barmpoutis, Panagiotis, et al. "Tropical Tree Species 3D Modelling and Classification Based on LiDAR Technology." Recent Advances in 3D Imaging, Modeling, and Reconstruction, edited by Athanasios Voulodimos and Anastasios Doulamis, IGI Global, 2020, pp. 1-22. https://doi.org/10.4018/978-1-5225-5294-9.ch001

APA

Barmpoutis, P., Stathaki, T., Lloyd, J., & Moura, M. S. (2020). Tropical Tree Species 3D Modelling and Classification Based on LiDAR Technology. In A. Voulodimos & A. Doulamis (Eds.), Recent Advances in 3D Imaging, Modeling, and Reconstruction (pp. 1-22). IGI Global. https://doi.org/10.4018/978-1-5225-5294-9.ch001

Chicago

Barmpoutis, Panagiotis, et al. "Tropical Tree Species 3D Modelling and Classification Based on LiDAR Technology." In Recent Advances in 3D Imaging, Modeling, and Reconstruction, edited by Athanasios Voulodimos and Anastasios Doulamis, 1-22. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-5225-5294-9.ch001

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Abstract

Over the last decade or so, laser scanning technology has become an increasingly popular and important tool for forestry inventory, enabling accurate capture of 3D information in a fast and environmentally friendly manner. To this end, the authors propose here a system for tropical tree species classification based on 3D scans of LiDAR sensing technology. In order to exploit the interrelated patterns of trees, skeleton representations of tree point clouds are extracted, and their structures are divided into overlapping equal-sized 3D segments. Subsequently, they represent them as third-order sparse structure tensors setting the value of skeleton coordinates equal to one. Based on the higher-order tensor decomposition of each sparse segment, they 1) estimate the mode-n singular values extracting intra-correlations of tree branches and 2) model tropical trees as linear dynamical systems extracting appearance information and dynamics. The proposed methodology was evaluated in tropical tree species and specifically in a dataset consisting of 26 point clouds of common Caatinga dry-forest trees.

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