Automatic tree detection in sample plots from a simple terrestrial laser scanning
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Pesquisa Florestal Brasileira (Online) |
Texto Completo: | https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1730 |
Resumo: | This study aimed the automatic identification of trees in circular sample units of 200, 300 and 400 m² in stands of Eucalyptus spp., using TLS (Terrestrial Laser Scanning) in Mato Grosso do Sul State, Brazil. Three planting ages were tested: 2 years-old-plantation, considering trees with natural pruning (E. urophylla -200 m²) and without natural pruning (E. grandis - 300 m²), and trees with 4.5 and with 5.5 years-old without pruning (hibrid E. urophylla x E. grandis - 400 m²). Field laser scanning was performed with Trimble TX5 equipment. This approach was based on a cut of point-cloud at 1.3 m above ground level (DBH) and the developing the algorithm 2D slice. It was possible to detect 98.3, 98 and 93.9% of trees for samples units of 200, 300 and 400 m², respectively. These identifications were influenced by the spatial distribution of trees because of the shading of trees further from the equipment. This simple scan should be applied only for small sample units. The error detections in areas greater than 200 m², may influence negatively the dendrometric estimations. |
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Automatic tree detection in sample plots from a simple terrestrial laser scanningDetecção automática de árvores em unidades amostrais a partir de varredura simples com laser terrestreSombreamentoEucalyptusRelevoShadingEucalyptusReliefThis study aimed the automatic identification of trees in circular sample units of 200, 300 and 400 m² in stands of Eucalyptus spp., using TLS (Terrestrial Laser Scanning) in Mato Grosso do Sul State, Brazil. Three planting ages were tested: 2 years-old-plantation, considering trees with natural pruning (E. urophylla -200 m²) and without natural pruning (E. grandis - 300 m²), and trees with 4.5 and with 5.5 years-old without pruning (hibrid E. urophylla x E. grandis - 400 m²). Field laser scanning was performed with Trimble TX5 equipment. This approach was based on a cut of point-cloud at 1.3 m above ground level (DBH) and the developing the algorithm 2D slice. It was possible to detect 98.3, 98 and 93.9% of trees for samples units of 200, 300 and 400 m², respectively. These identifications were influenced by the spatial distribution of trees because of the shading of trees further from the equipment. This simple scan should be applied only for small sample units. The error detections in areas greater than 200 m², may influence negatively the dendrometric estimations.O objetivo deste estudo foi a identificação automática de árvores em unidades amostrais circulares de 200, 300 e 400 m² em povoamentos de Eucalyptus spp. a partir de dados de TLS (Terrestrial Laser Scanning) no estado do Mato Grosso do Sul. Foram testadas três idades de plantio: árvores com 2 anos, sendo consideradas com desrama natural (E. urophylla) e sem desrama natural (E. grandis); árvores com 4,5 e com 5,5 anos, sem desrama (hibrido E. urophylla x E. grandis). A varredura laser em campo foi realizada com o equipamento Trimble TX5. Para a identificação automática das árvores, foi realizado um recorte na nuvem de pontos a 1,30 m do solo (DAP) e desenvolvido o algoritmo denominado fatia 2D. Foi possível a detecção de 98,3, 98 e 93,9% das árvores para as unidades amostrais de 200, 300 e 400 m², respectivamente. A distribuição espacial das árvores no plantio influenciou a identificação, ocasionando sombreamento das árvores mais distantes do equipamento laser. A adoção de varreduras simples deve ser aplicada somente em unidades amostrais pequenas, pois unidades amostrais acima de 200 m² acarretam maiores erros de detecção de árvores, o que pode gerar informações equivocadas nas estimativas dendrométricas da floresta.Embrapa Florestas2019-12-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/173010.4336/2019.pfb.39e201801730Pesquisa Florestal Brasileira; v. 39 (2019)Pesquisa Florestal Brasileira; Vol. 39 (2019)1983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1730/909https://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessPesck, Vagner AlexLingnau, ChristelMachado, Alvaro Muriel LimaFigueiredo Filho, AfonsoStepka, Thiago Floriani2020-01-02T11:18:34Zoai:pfb.cnpf.embrapa.br/pfb:article/1730Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2020-01-02T11:18:34Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Automatic tree detection in sample plots from a simple terrestrial laser scanning Detecção automática de árvores em unidades amostrais a partir de varredura simples com laser terrestre |
title |
Automatic tree detection in sample plots from a simple terrestrial laser scanning |
spellingShingle |
Automatic tree detection in sample plots from a simple terrestrial laser scanning Pesck, Vagner Alex Sombreamento Eucalyptus Relevo Shading Eucalyptus Relief |
title_short |
Automatic tree detection in sample plots from a simple terrestrial laser scanning |
title_full |
Automatic tree detection in sample plots from a simple terrestrial laser scanning |
title_fullStr |
Automatic tree detection in sample plots from a simple terrestrial laser scanning |
title_full_unstemmed |
Automatic tree detection in sample plots from a simple terrestrial laser scanning |
title_sort |
Automatic tree detection in sample plots from a simple terrestrial laser scanning |
author |
Pesck, Vagner Alex |
author_facet |
Pesck, Vagner Alex Lingnau, Christel Machado, Alvaro Muriel Lima Figueiredo Filho, Afonso Stepka, Thiago Floriani |
author_role |
author |
author2 |
Lingnau, Christel Machado, Alvaro Muriel Lima Figueiredo Filho, Afonso Stepka, Thiago Floriani |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Pesck, Vagner Alex Lingnau, Christel Machado, Alvaro Muriel Lima Figueiredo Filho, Afonso Stepka, Thiago Floriani |
dc.subject.por.fl_str_mv |
Sombreamento Eucalyptus Relevo Shading Eucalyptus Relief |
topic |
Sombreamento Eucalyptus Relevo Shading Eucalyptus Relief |
description |
This study aimed the automatic identification of trees in circular sample units of 200, 300 and 400 m² in stands of Eucalyptus spp., using TLS (Terrestrial Laser Scanning) in Mato Grosso do Sul State, Brazil. Three planting ages were tested: 2 years-old-plantation, considering trees with natural pruning (E. urophylla -200 m²) and without natural pruning (E. grandis - 300 m²), and trees with 4.5 and with 5.5 years-old without pruning (hibrid E. urophylla x E. grandis - 400 m²). Field laser scanning was performed with Trimble TX5 equipment. This approach was based on a cut of point-cloud at 1.3 m above ground level (DBH) and the developing the algorithm 2D slice. It was possible to detect 98.3, 98 and 93.9% of trees for samples units of 200, 300 and 400 m², respectively. These identifications were influenced by the spatial distribution of trees because of the shading of trees further from the equipment. This simple scan should be applied only for small sample units. The error detections in areas greater than 200 m², may influence negatively the dendrometric estimations. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-31 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1730 10.4336/2019.pfb.39e201801730 |
url |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1730 |
identifier_str_mv |
10.4336/2019.pfb.39e201801730 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1730/909 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Embrapa Florestas |
publisher.none.fl_str_mv |
Embrapa Florestas |
dc.source.none.fl_str_mv |
Pesquisa Florestal Brasileira; v. 39 (2019) Pesquisa Florestal Brasileira; Vol. 39 (2019) 1983-2605 1809-3647 reponame:Pesquisa Florestal Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Florestal Brasileira (Online) |
collection |
Pesquisa Florestal Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br |
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1783370936834064384 |