Identificação de árvores individuais a partir de levantamentos laser aerotransportado por meio de janela inversa
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
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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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 |
_version_ |
1815438959835086848 |