Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa

Detalhes bibliográficos
Autor(a) principal: Gorgens, Eric Bastos
Data de Publicação: 2016
Outros Autores: Rodriguez, Luiz Carlos Estraviz, Silva, André Gracioso Peres da, Silva, Carlos Alberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/14951
Resumo: The local maximum filtering performance is highly dependent of the window size definition. This paper proposes that the window size should be determined by an inverse relationship to the canopy height model, and test the hypothesis that a windowsize inversely proportional will have better performance than the window proportional to the canopy height model. The study area is located in the southeastern region of the State of British Columbia, Canada. The natural vegetation is the boreal type and is characterized by the dominance of two species Picea engelmannii Parry ex. Engelmann (Engelmann spruce) and Abies lasiocarpa (Hook.) Nutt. (sub-alpine fir). The relief is mountainous with altitudes ranging from 650-2400 meters. 62 plots with 256 square meters were measured in the field. The airborne LiDAR had discrete returns, 2 points per square meter density and small-footprint. The performance of the search windows was evaluated based on success percentage, absolute average error and also compared to the observed values of the field plots. The local maximum filter underestimated the number of trees per hectare for both window sizing methods. The use of the inverse proportional window size has resulted in superior results, particularly for regions with highest density of trees.
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spelling Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversaIndividual tree identification in airborne laser data by inverse search windowLIDARMáximo localModelo digital de alturasLight detection and rangingLocal maximumCanopy height modelAirborne laser scanningThe local maximum filtering performance is highly dependent of the window size definition. This paper proposes that the window size should be determined by an inverse relationship to the canopy height model, and test the hypothesis that a windowsize inversely proportional will have better performance than the window proportional to the canopy height model. The study area is located in the southeastern region of the State of British Columbia, Canada. The natural vegetation is the boreal type and is characterized by the dominance of two species Picea engelmannii Parry ex. Engelmann (Engelmann spruce) and Abies lasiocarpa (Hook.) Nutt. (sub-alpine fir). The relief is mountainous with altitudes ranging from 650-2400 meters. 62 plots with 256 square meters were measured in the field. The airborne LiDAR had discrete returns, 2 points per square meter density and small-footprint. The performance of the search windows was evaluated based on success percentage, absolute average error and also compared to the observed values of the field plots. The local maximum filter underestimated the number of trees per hectare for both window sizing methods. The use of the inverse proportional window size has resulted in superior results, particularly for regions with highest density of trees.Universidade Federal de Lavras (UFLA)2016-04-072017-08-01T20:19:38Z2017-08-01T20:19:38Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfGORGENS, E. B. et al. Individual tree identification in airborne laser data by inverse search window. CERNE, Lavras, v. 21, n. 1, Jan./Mar. 2015. DOI: 10.1590/01047760201521011535.http://repositorio.ufla.br/jspui/handle/1/14951CERNE; Vol 21 No 1 (2015); 91-96CERNE; Vol 21 No 1 (2015); 91-962317-63420104-7760reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAengCopyright (c) 2016 CERNEhttp://creativecommons.org/licenses/by/4.0/Attribution 4.0 Internationalinfo:eu-repo/semantics/openAccessGorgens, Eric BastosRodriguez, Luiz Carlos EstravizSilva, André Gracioso Peres daSilva, Carlos Alberto2021-01-19T18:57:33Zoai:localhost:1/14951Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-01-19T18:57:33Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
Individual tree identification in airborne laser data by inverse search window
title Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
spellingShingle Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
Gorgens, Eric Bastos
LIDAR
Máximo local
Modelo digital de alturas
Light detection and ranging
Local maximum
Canopy height model
Airborne laser scanning
title_short Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
title_full Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
title_fullStr Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
title_full_unstemmed Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
title_sort Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
author Gorgens, Eric Bastos
author_facet Gorgens, Eric Bastos
Rodriguez, Luiz Carlos Estraviz
Silva, André Gracioso Peres da
Silva, Carlos Alberto
author_role author
author2 Rodriguez, Luiz Carlos Estraviz
Silva, André Gracioso Peres da
Silva, Carlos Alberto
author2_role author
author
author
dc.contributor.author.fl_str_mv Gorgens, Eric Bastos
Rodriguez, Luiz Carlos Estraviz
Silva, André Gracioso Peres da
Silva, Carlos Alberto
dc.subject.por.fl_str_mv LIDAR
Máximo local
Modelo digital de alturas
Light detection and ranging
Local maximum
Canopy height model
Airborne laser scanning
topic LIDAR
Máximo local
Modelo digital de alturas
Light detection and ranging
Local maximum
Canopy height model
Airborne laser scanning
description The local maximum filtering performance is highly dependent of the window size definition. This paper proposes that the window size should be determined by an inverse relationship to the canopy height model, and test the hypothesis that a windowsize inversely proportional will have better performance than the window proportional to the canopy height model. The study area is located in the southeastern region of the State of British Columbia, Canada. The natural vegetation is the boreal type and is characterized by the dominance of two species Picea engelmannii Parry ex. Engelmann (Engelmann spruce) and Abies lasiocarpa (Hook.) Nutt. (sub-alpine fir). The relief is mountainous with altitudes ranging from 650-2400 meters. 62 plots with 256 square meters were measured in the field. The airborne LiDAR had discrete returns, 2 points per square meter density and small-footprint. The performance of the search windows was evaluated based on success percentage, absolute average error and also compared to the observed values of the field plots. The local maximum filter underestimated the number of trees per hectare for both window sizing methods. The use of the inverse proportional window size has resulted in superior results, particularly for regions with highest density of trees.
publishDate 2016
dc.date.none.fl_str_mv 2016-04-07
2017-08-01T20:19:38Z
2017-08-01T20:19:38Z
2017-08-01
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 GORGENS, E. B. et al. Individual tree identification in airborne laser data by inverse search window. CERNE, Lavras, v. 21, n. 1, Jan./Mar. 2015. DOI: 10.1590/01047760201521011535.
http://repositorio.ufla.br/jspui/handle/1/14951
identifier_str_mv GORGENS, E. B. et al. Individual tree identification in airborne laser data by inverse search window. CERNE, Lavras, v. 21, n. 1, Jan./Mar. 2015. DOI: 10.1590/01047760201521011535.
url http://repositorio.ufla.br/jspui/handle/1/14951
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Copyright (c) 2016 CERNE
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 CERNE
http://creativecommons.org/licenses/by/4.0/
Attribution 4.0 International
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA)
publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA)
dc.source.none.fl_str_mv CERNE; Vol 21 No 1 (2015); 91-96
CERNE; Vol 21 No 1 (2015); 91-96
2317-6342
0104-7760
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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