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Tropical Tree Species 3D Modelling and Classification Based on LiDAR Technology
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Author(s): Panagiotis Barmpoutis (Imperial College London, UK), Tania Stathaki (Imperial College London, UK), Jonathan Lloyd (Imperial College London, UK)and Magna Soelma Bessera de Moura (Brazilian Agricultural Research Corporation, Brazil)
Copyright: 2020
Pages: 22
Source title:
Recent Advances in 3D Imaging, Modeling, and Reconstruction
Source Author(s)/Editor(s): Athanasios Voulodimos (University of West Attica, Athens, Greece)and Anastasios Doulamis (National Technical University of Athens, Athens, Greece)
DOI: 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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