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| Registros recuperados : 115 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
05/03/2021 |
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Data da última atualização: |
05/03/2021 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
BARMPOUTIS, P.; STATHAKI, T.; LLOYD; MOURA, M. S. B. de. |
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Afiliação: |
Panagiotis Barmpoutis; Tania Stathaki; Jonathan Lloyd; MAGNA SOELMA BESERRA DE MOURA, CPATSA. |
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Título: |
Tropical tree species 3D modelling and classification based on LiDAR technology. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
In: VOULODIMOS, A.; DOULAMIS, A. (Ed.). Recent advances in 3D imaging, modeling, and reconstruction. Pensilvânia: IGI Global, 2020. |
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Páginas: |
cap. 1, p. 1-22. |
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DOI: |
0.4018/978-1-5225-5294-9.ch001 |
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Idioma: |
Inglês |
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Conteúdo: |
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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Palavras-Chave: |
Floresta seca; Modelagem; Tecnologia LiDAR. |
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Thesagro: |
Caatinga; Floresta; Floresta Tropical; Inventário Florestal. |
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Thesaurus NAL: |
Dry forests; Forestry. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02001naa a2200289 a 4500
001 2130505
005 2021-03-05
008 2020 bl uuuu u00u1 u #d
024 7 $a0.4018/978-1-5225-5294-9.ch001$2DOI
100 1 $aBARMPOUTIS, P.
245 $aTropical tree species 3D modelling and classification based on LiDAR technology.$h[electronic resource]
260 $c2020
300 $acap. 1, p. 1-22.
520 $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 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.
650 $aDry forests
650 $aForestry
650 $aCaatinga
650 $aFloresta
650 $aFloresta Tropical
650 $aInventário Florestal
653 $aFloresta seca
653 $aModelagem
653 $aTecnologia LiDAR
700 1 $aSTATHAKI, T.
700 1 $aLLOYD
700 1 $aMOURA, M. S. B. de
773 $tIn: VOULODIMOS, A.; DOULAMIS, A. (Ed.). Recent advances in 3D imaging, modeling, and reconstruction. Pensilvânia: IGI Global, 2020.
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