AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Boletim de Ciências Geodésicas |
Texto Completo: | https://revistas.ufpr.br/bcg/article/view/84202 |
Resumo: | This work aims to analyze the potential of the Photogrammetric Point Cloud (PPC) obtained from Remote Piloted Aircraft (RPA) optical images for detecting and obtaining tree heights in a loblolly pine plantation using a global maximum filter. The enhanced algorithm used in this study is then named STD (Single Tree Detection). Field surveys were conducted to count all the trees in the field (Forest Census) and measure the trees’ height with a vertex hypsometer. The results were faced to PCC outcomes. The detection rate (r) was equal to the precision rate (p), indicating that the algorithm reaches a high tree detection performance. In summary, the STD algorithm segmented 2,192 trees, representing 89% of trees recorded in the forest census. The retrieved tree height reached, on average, a height of 17.05 m, whereas slightly higher by the traditional forest inventory (17.42 m). The root-mean-square error (RMSE) and Bias were 47 cm (2.8%) and -37 cm (-2.2%), respectively. The Dunnett test showed that the tree height did not significantly differ between the results obtained by traditional forest inventory from those generated by the STD. It confirms the potential use of PPC for forest inventory procedures. |
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AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDSGeociências, Ciências da TerraForest census; Loblolly pine; Global maximum filter; tree height; RPAThis work aims to analyze the potential of the Photogrammetric Point Cloud (PPC) obtained from Remote Piloted Aircraft (RPA) optical images for detecting and obtaining tree heights in a loblolly pine plantation using a global maximum filter. The enhanced algorithm used in this study is then named STD (Single Tree Detection). Field surveys were conducted to count all the trees in the field (Forest Census) and measure the trees’ height with a vertex hypsometer. The results were faced to PCC outcomes. The detection rate (r) was equal to the precision rate (p), indicating that the algorithm reaches a high tree detection performance. In summary, the STD algorithm segmented 2,192 trees, representing 89% of trees recorded in the forest census. The retrieved tree height reached, on average, a height of 17.05 m, whereas slightly higher by the traditional forest inventory (17.42 m). The root-mean-square error (RMSE) and Bias were 47 cm (2.8%) and -37 cm (-2.2%), respectively. The Dunnett test showed that the tree height did not significantly differ between the results obtained by traditional forest inventory from those generated by the STD. It confirms the potential use of PPC for forest inventory procedures.Boletim de Ciências GeodésicasBulletin of Geodetic SciencesCAPESSantos, Kênia Samara MourãoLingnau, ChristelSantos, Daniel Rodrigues dos2022-01-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufpr.br/bcg/article/view/84202Boletim de Ciências Geodésicas; Vol 27, No 3 (2021)Bulletin of Geodetic Sciences; Vol 27, No 3 (2021)1982-21701413-4853reponame:Boletim de Ciências Geodésicasinstname:Universidade Federal do Paraná (UFPR)instacron:UFPRenghttps://revistas.ufpr.br/bcg/article/view/84202/45597Copyright (c) 2022 Kênia Samara Mourão Santos, Christel Lingnau, Daniel Rodrigues dos Santoshttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccess2022-01-03T16:07:24Zoai:revistas.ufpr.br:article/84202Revistahttps://revistas.ufpr.br/bcgPUBhttps://revistas.ufpr.br/bcg/oaiqdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br1982-21701413-4853opendoar:2022-01-03T16:07:24Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)false |
dc.title.none.fl_str_mv |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
title |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
spellingShingle |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS Santos, Kênia Samara Mourão Geociências, Ciências da Terra Forest census; Loblolly pine; Global maximum filter; tree height; RPA |
title_short |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
title_full |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
title_fullStr |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
title_full_unstemmed |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
title_sort |
AUTOMATIC DETECTION OF PLANTED TREES AND THEIR HEIGHTS USING PHOTOGRAMMETRIC RPA POINT CLOUDS |
author |
Santos, Kênia Samara Mourão |
author_facet |
Santos, Kênia Samara Mourão Lingnau, Christel Santos, Daniel Rodrigues dos |
author_role |
author |
author2 |
Lingnau, Christel Santos, Daniel Rodrigues dos |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
CAPES |
dc.contributor.author.fl_str_mv |
Santos, Kênia Samara Mourão Lingnau, Christel Santos, Daniel Rodrigues dos |
dc.subject.por.fl_str_mv |
Geociências, Ciências da Terra Forest census; Loblolly pine; Global maximum filter; tree height; RPA |
topic |
Geociências, Ciências da Terra Forest census; Loblolly pine; Global maximum filter; tree height; RPA |
description |
This work aims to analyze the potential of the Photogrammetric Point Cloud (PPC) obtained from Remote Piloted Aircraft (RPA) optical images for detecting and obtaining tree heights in a loblolly pine plantation using a global maximum filter. The enhanced algorithm used in this study is then named STD (Single Tree Detection). Field surveys were conducted to count all the trees in the field (Forest Census) and measure the trees’ height with a vertex hypsometer. The results were faced to PCC outcomes. The detection rate (r) was equal to the precision rate (p), indicating that the algorithm reaches a high tree detection performance. In summary, the STD algorithm segmented 2,192 trees, representing 89% of trees recorded in the forest census. The retrieved tree height reached, on average, a height of 17.05 m, whereas slightly higher by the traditional forest inventory (17.42 m). The root-mean-square error (RMSE) and Bias were 47 cm (2.8%) and -37 cm (-2.2%), respectively. The Dunnett test showed that the tree height did not significantly differ between the results obtained by traditional forest inventory from those generated by the STD. It confirms the potential use of PPC for forest inventory procedures. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-03 |
dc.type.none.fl_str_mv |
|
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://revistas.ufpr.br/bcg/article/view/84202 |
url |
https://revistas.ufpr.br/bcg/article/view/84202 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/84202/45597 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Kênia Samara Mourão Santos, Christel Lingnau, Daniel Rodrigues dos Santos http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Kênia Samara Mourão Santos, Christel Lingnau, Daniel Rodrigues dos Santos http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
dc.source.none.fl_str_mv |
Boletim de Ciências Geodésicas; Vol 27, No 3 (2021) Bulletin of Geodetic Sciences; Vol 27, No 3 (2021) 1982-2170 1413-4853 reponame:Boletim de Ciências Geodésicas instname:Universidade Federal do Paraná (UFPR) instacron:UFPR |
instname_str |
Universidade Federal do Paraná (UFPR) |
instacron_str |
UFPR |
institution |
UFPR |
reponame_str |
Boletim de Ciências Geodésicas |
collection |
Boletim de Ciências Geodésicas |
repository.name.fl_str_mv |
Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR) |
repository.mail.fl_str_mv |
qdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br |
_version_ |
1799771720070987776 |