02252naa a2200337 a 450000100080000000500110000800800410001902400410006010000190010124501080012026000090022830000250023752011130026265000130137565000220138865000350141065000280144565000190147365000130149265000330150565000130153865000130155165000260156465300230159065300350161365300210164870000170166970000140168670000230170077301910172321505882023-01-03       2022    bl uuuu     u00u1 u    #d7 a10.4018/978-1-6684-5678-1.ch0172DOI1 aBARMPOUTIS, P.  aTropical tree species 3D modelling and classification based on LiDAR technology.h[electronic resource]  c2022  acap. 17, p. 326-346.  aOver 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 overlap- ping 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.  aForestry  aNatural resources  aNatural resources conservation  aSustainable development  aBiodiversidade  aCaatinga  aDesenvolvimento Sustentável  aEcologia  aFloresta  aInventário Florestal  aÁrvores tropicais  aTecnologia de detecção LiDAR  aUso Sustentável1 aSTATHAKI, T.1 aLLOYD, J.1 aMOURA, M. S. B. de  tIn: INFORMATION RESOURCES MANAGEMENT ASSOCIATION. Research anthology on ecosystem conservation and preserving biodiversity. Pensilvânia: IGI Global: Engineering Science Reference, 2022.