Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data

Detalhes bibliográficos
Autor(a) principal: Rex,Franciel Eduardo
Data de Publicação: 2019
Outros Autores: Corte,Ana Paula Dalla, Machado,Sebastião do Amaral, Silva,Carlos Alberto, Sanquetta,Carlos Roberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Floresta e Ambiente
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000400142
Resumo: ABSTRACT The objective of this study was to test the performance of canopy data obtained from Airborne Laser Scanner (ALS) in generating estimates of above-ground biomass (AGB) of Araucaria angustifolia (Bertol.) Kuntze individuals. A cloud of ALS points located in a fragment of native urban forest in Curitiba, Paraná was used. The procedures consisted of: classifying points; obtaining and smoothing the Canopy Height Model (CHM); detecting peaks and segmenting canopy using eCognition software. Mathematical models were adjusted to estimate the AGB from the crown areas. Two equations were required to estimate the individual AGB, while R2 (%) values of 96.19 and 98.89 were found. The total AGB stock found was 264.333 kg. The LiDAR technology and the methods for obtaining the information used in this work constitute non-destructive and precise tools for quantifying biomass in native forests.
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spelling Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Datanative forestestimation equationsremote sensingABSTRACT The objective of this study was to test the performance of canopy data obtained from Airborne Laser Scanner (ALS) in generating estimates of above-ground biomass (AGB) of Araucaria angustifolia (Bertol.) Kuntze individuals. A cloud of ALS points located in a fragment of native urban forest in Curitiba, Paraná was used. The procedures consisted of: classifying points; obtaining and smoothing the Canopy Height Model (CHM); detecting peaks and segmenting canopy using eCognition software. Mathematical models were adjusted to estimate the AGB from the crown areas. Two equations were required to estimate the individual AGB, while R2 (%) values of 96.19 and 98.89 were found. The total AGB stock found was 264.333 kg. The LiDAR technology and the methods for obtaining the information used in this work constitute non-destructive and precise tools for quantifying biomass in native forests.Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000400142Floresta e Ambiente v.26 n.4 2019reponame:Floresta e Ambienteinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ10.1590/2179-8087.110717info:eu-repo/semantics/openAccessRex,Franciel EduardoCorte,Ana Paula DallaMachado,Sebastião do AmaralSilva,Carlos AlbertoSanquetta,Carlos Robertoeng2019-09-19T00:00:00Zoai:scielo:S2179-80872019000400142Revistahttps://www.floram.org/PUBhttps://old.scielo.br/oai/scielo-oai.phpfloramjournal@gmail.com||floram@ufrrj.br||2179-80871415-0980opendoar:2019-09-19T00:00Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
title Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
spellingShingle Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
Rex,Franciel Eduardo
native forest
estimation equations
remote sensing
title_short Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
title_full Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
title_fullStr Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
title_full_unstemmed Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
title_sort Estimating Above-Ground Biomass of Araucaria angustifolia (Bertol.) Kuntze Using LiDAR Data
author Rex,Franciel Eduardo
author_facet Rex,Franciel Eduardo
Corte,Ana Paula Dalla
Machado,Sebastião do Amaral
Silva,Carlos Alberto
Sanquetta,Carlos Roberto
author_role author
author2 Corte,Ana Paula Dalla
Machado,Sebastião do Amaral
Silva,Carlos Alberto
Sanquetta,Carlos Roberto
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Rex,Franciel Eduardo
Corte,Ana Paula Dalla
Machado,Sebastião do Amaral
Silva,Carlos Alberto
Sanquetta,Carlos Roberto
dc.subject.por.fl_str_mv native forest
estimation equations
remote sensing
topic native forest
estimation equations
remote sensing
description ABSTRACT The objective of this study was to test the performance of canopy data obtained from Airborne Laser Scanner (ALS) in generating estimates of above-ground biomass (AGB) of Araucaria angustifolia (Bertol.) Kuntze individuals. A cloud of ALS points located in a fragment of native urban forest in Curitiba, Paraná was used. The procedures consisted of: classifying points; obtaining and smoothing the Canopy Height Model (CHM); detecting peaks and segmenting canopy using eCognition software. Mathematical models were adjusted to estimate the AGB from the crown areas. Two equations were required to estimate the individual AGB, while R2 (%) values of 96.19 and 98.89 were found. The total AGB stock found was 264.333 kg. The LiDAR technology and the methods for obtaining the information used in this work constitute non-destructive and precise tools for quantifying biomass in native forests.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000400142
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000400142
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2179-8087.110717
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
publisher.none.fl_str_mv Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
dc.source.none.fl_str_mv Floresta e Ambiente v.26 n.4 2019
reponame:Floresta e Ambiente
instname:Universidade Federal do Rio de Janeiro (UFRJ)
instacron:UFRJ
instname_str Universidade Federal do Rio de Janeiro (UFRJ)
instacron_str UFRJ
institution UFRJ
reponame_str Floresta e Ambiente
collection Floresta e Ambiente
repository.name.fl_str_mv Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)
repository.mail.fl_str_mv floramjournal@gmail.com||floram@ufrrj.br||
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