MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Cerne (Online) |
Texto Completo: | https://cerne.ufla.br/site/index.php/CERNE/article/view/1029 |
Resumo: | The volumetric estimate from digital scanning of the forests through the use of LIDAR increases the precision of forest management techniques in planning tropical forest logging operations. The use of this remote detection technology allows the incorporation of crown morphometric variables which are still little known and little used due to the difficulty of collecting field data for volume equations. The objective of this study was to build equations capable of estimating the stem volume of dominant and codominant individual trees from the crown’s morphometry obtained by airborne LIDAR, considering two forest inventory situations: a) with the collection of diameter at breast height (DBH), and crown morphometric variables obtained from LIDAR data and b) using only the crown morphometry variables. For the selection of models the factors considered were: the correlation matrix of predictor variables and the combination of variables that generates the best results by statistical criteria Syx, Syx (%) and Pressp, and that were homoscedastic and had a normal and independent distribution of errors. The influence analysis was performed for the best equations. The results for the statistical fit of the equations to the two situations allowed the selection of models with and without DBH, with R2 aj.(%) values of a) 92.92 and b) 79.44, Syx(%) values of a) 16.73 and b) 27.47, and, Pressp criterion values of a) 201.15 m6 and b) 537.47 m6, respectively. Through morphometric variables it was possible to develop equations capable of accurately estimating the stem volume of dominant and codominant trees in tropical forests. |
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MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDARLaser profilingregression analysisprecision forestryAmazon.The volumetric estimate from digital scanning of the forests through the use of LIDAR increases the precision of forest management techniques in planning tropical forest logging operations. The use of this remote detection technology allows the incorporation of crown morphometric variables which are still little known and little used due to the difficulty of collecting field data for volume equations. The objective of this study was to build equations capable of estimating the stem volume of dominant and codominant individual trees from the crown’s morphometry obtained by airborne LIDAR, considering two forest inventory situations: a) with the collection of diameter at breast height (DBH), and crown morphometric variables obtained from LIDAR data and b) using only the crown morphometry variables. For the selection of models the factors considered were: the correlation matrix of predictor variables and the combination of variables that generates the best results by statistical criteria Syx, Syx (%) and Pressp, and that were homoscedastic and had a normal and independent distribution of errors. The influence analysis was performed for the best equations. The results for the statistical fit of the equations to the two situations allowed the selection of models with and without DBH, with R2 aj.(%) values of a) 92.92 and b) 79.44, Syx(%) values of a) 16.73 and b) 27.47, and, Pressp criterion values of a) 201.15 m6 and b) 537.47 m6, respectively. Through morphometric variables it was possible to develop equations capable of accurately estimating the stem volume of dominant and codominant trees in tropical forests.CERNECERNE2016-04-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/1029CERNE; Vol. 20 No. 4 (2014); 621-628CERNE; v. 20 n. 4 (2014); 621-6282317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/1029/800Copyright (c) 2016 CERNEinfo:eu-repo/semantics/openAccessFigueiredo, Evandro Orfanód´Oliveira, Marcus Vinicio NevesFearnside, Philip MartinPapa, Daniel de Almeida2016-04-20T10:16:00Zoai:cerne.ufla.br:article/1029Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:19.587807Cerne (Online) - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
title |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
spellingShingle |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR Figueiredo, Evandro Orfanó Laser profiling regression analysis precision forestry Amazon. |
title_short |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
title_full |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
title_fullStr |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
title_full_unstemmed |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
title_sort |
MODELS TO ESTIMATIVE VOLUME OF INDIVIDUAL TREES BY MORPHOMETRY OF CROWNS OBTAINED WITH LIDAR |
author |
Figueiredo, Evandro Orfanó |
author_facet |
Figueiredo, Evandro Orfanó d´Oliveira, Marcus Vinicio Neves Fearnside, Philip Martin Papa, Daniel de Almeida |
author_role |
author |
author2 |
d´Oliveira, Marcus Vinicio Neves Fearnside, Philip Martin Papa, Daniel de Almeida |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Figueiredo, Evandro Orfanó d´Oliveira, Marcus Vinicio Neves Fearnside, Philip Martin Papa, Daniel de Almeida |
dc.subject.por.fl_str_mv |
Laser profiling regression analysis precision forestry Amazon. |
topic |
Laser profiling regression analysis precision forestry Amazon. |
description |
The volumetric estimate from digital scanning of the forests through the use of LIDAR increases the precision of forest management techniques in planning tropical forest logging operations. The use of this remote detection technology allows the incorporation of crown morphometric variables which are still little known and little used due to the difficulty of collecting field data for volume equations. The objective of this study was to build equations capable of estimating the stem volume of dominant and codominant individual trees from the crown’s morphometry obtained by airborne LIDAR, considering two forest inventory situations: a) with the collection of diameter at breast height (DBH), and crown morphometric variables obtained from LIDAR data and b) using only the crown morphometry variables. For the selection of models the factors considered were: the correlation matrix of predictor variables and the combination of variables that generates the best results by statistical criteria Syx, Syx (%) and Pressp, and that were homoscedastic and had a normal and independent distribution of errors. The influence analysis was performed for the best equations. The results for the statistical fit of the equations to the two situations allowed the selection of models with and without DBH, with R2 aj.(%) values of a) 92.92 and b) 79.44, Syx(%) values of a) 16.73 and b) 27.47, and, Pressp criterion values of a) 201.15 m6 and b) 537.47 m6, respectively. Through morphometric variables it was possible to develop equations capable of accurately estimating the stem volume of dominant and codominant trees in tropical forests. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-04-07 |
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://cerne.ufla.br/site/index.php/CERNE/article/view/1029 |
url |
https://cerne.ufla.br/site/index.php/CERNE/article/view/1029 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://cerne.ufla.br/site/index.php/CERNE/article/view/1029/800 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 CERNE info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 CERNE |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
CERNE CERNE |
publisher.none.fl_str_mv |
CERNE CERNE |
dc.source.none.fl_str_mv |
CERNE; Vol. 20 No. 4 (2014); 621-628 CERNE; v. 20 n. 4 (2014); 621-628 2317-6342 0104-7760 reponame:Cerne (Online) instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Cerne (Online) |
collection |
Cerne (Online) |
repository.name.fl_str_mv |
Cerne (Online) - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
cerne@dcf.ufla.br||cerne@dcf.ufla.br |
_version_ |
1799874942443978752 |