Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data

Detalhes bibliográficos
Autor(a) principal: Rex, Franciel Eduardo
Data de Publicação: 2020
Outros Autores: Corte, Ana Paula Dalla, Silva, Carlos Alberto, Machado, Sebastião do Amaral, Sanquetta, Carlos Roberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anuário do Instituto de Geociências (Online)
Texto Completo: https://revistas.ufrj.br/index.php/aigeo/article/view/34207
Resumo: Tropical forest biomass plays an important role in the global carbon cycle. Thus, a better understanding of variations in the stocks, dynamics and structure of tropical forests is important to understanding the global carbon cycle. In this sense, the objective of this study was to evaluate the dynamics of above-ground biomass (AGB) in a rainforest using LiDAR (Light Detection and Ranging) data over a period of two years (2011-2013). Automatic crown detection techniques were used in a complementary way to observe whether structural changes may influence the dynamics of AGB. The study was conducted in Jamari National Forest in Rondonia. The methodology was composed of LiDAR processing and classification of objects (Crowns). Estimates of AGB were generated via LiDAR for the forest inventory plots and for the sample of the study area. Strong correlations were observed between estimates of AGB (r 0.88). The structural changes identified in the outlined crowns did not influence the values obtained for the sample area, which presented a reduction pattern (5.64%). Despite the negative changes that occurred in this study, no significant difference (p 0.05; Tukey test) of AGB was found among the evaluated period. The LiDAR technology has great potential for detecting large- scale changes and it is possible to obtain accurate environmental information (AGB). The approach used in the study may contribute for further analyses aimed at evaluating changes in AGB stock.
id UFRJ-21_3404797878f7413d46a8cc756c6fae3d
oai_identifier_str oai:www.revistas.ufrj.br:article/34207
network_acronym_str UFRJ-21
network_name_str Anuário do Instituto de Geociências (Online)
repository_id_str
spelling Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR DataAmazon; Inventory; LaserTropical forest biomass plays an important role in the global carbon cycle. Thus, a better understanding of variations in the stocks, dynamics and structure of tropical forests is important to understanding the global carbon cycle. In this sense, the objective of this study was to evaluate the dynamics of above-ground biomass (AGB) in a rainforest using LiDAR (Light Detection and Ranging) data over a period of two years (2011-2013). Automatic crown detection techniques were used in a complementary way to observe whether structural changes may influence the dynamics of AGB. The study was conducted in Jamari National Forest in Rondonia. The methodology was composed of LiDAR processing and classification of objects (Crowns). Estimates of AGB were generated via LiDAR for the forest inventory plots and for the sample of the study area. Strong correlations were observed between estimates of AGB (r 0.88). The structural changes identified in the outlined crowns did not influence the values obtained for the sample area, which presented a reduction pattern (5.64%). Despite the negative changes that occurred in this study, no significant difference (p 0.05; Tukey test) of AGB was found among the evaluated period. The LiDAR technology has great potential for detecting large- scale changes and it is possible to obtain accurate environmental information (AGB). The approach used in the study may contribute for further analyses aimed at evaluating changes in AGB stock.Universidade Federal do Rio de JaneiroRex, Franciel EduardoCorte, Ana Paula DallaSilva, Carlos AlbertoMachado, Sebastião do AmaralSanquetta, Carlos Roberto2020-04-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/3420710.11137/2020_1_228_238Anuário do Instituto de Geociências; Vol 43, No 1 (2020); 228-238Anuário do Instituto de Geociências; Vol 43, No 1 (2020); 228-2381982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJenghttps://revistas.ufrj.br/index.php/aigeo/article/view/34207/19123Copyright (c) 2020 Anuário do Instituto de Geociênciashttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccess2020-08-12T18:39:38Zoai:www.revistas.ufrj.br:article/34207Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2020-08-12T18:39:38Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv
Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
title Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
spellingShingle Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
Rex, Franciel Eduardo
Amazon; Inventory; Laser
title_short Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
title_full Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
title_fullStr Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
title_full_unstemmed Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
title_sort Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
author Rex, Franciel Eduardo
author_facet Rex, Franciel Eduardo
Corte, Ana Paula Dalla
Silva, Carlos Alberto
Machado, Sebastião do Amaral
Sanquetta, Carlos Roberto
author_role author
author2 Corte, Ana Paula Dalla
Silva, Carlos Alberto
Machado, Sebastião do Amaral
Sanquetta, Carlos Roberto
author2_role author
author
author
author
dc.contributor.none.fl_str_mv

dc.contributor.author.fl_str_mv Rex, Franciel Eduardo
Corte, Ana Paula Dalla
Silva, Carlos Alberto
Machado, Sebastião do Amaral
Sanquetta, Carlos Roberto
dc.subject.none.fl_str_mv
dc.subject.por.fl_str_mv Amazon; Inventory; Laser
topic Amazon; Inventory; Laser
description Tropical forest biomass plays an important role in the global carbon cycle. Thus, a better understanding of variations in the stocks, dynamics and structure of tropical forests is important to understanding the global carbon cycle. In this sense, the objective of this study was to evaluate the dynamics of above-ground biomass (AGB) in a rainforest using LiDAR (Light Detection and Ranging) data over a period of two years (2011-2013). Automatic crown detection techniques were used in a complementary way to observe whether structural changes may influence the dynamics of AGB. The study was conducted in Jamari National Forest in Rondonia. The methodology was composed of LiDAR processing and classification of objects (Crowns). Estimates of AGB were generated via LiDAR for the forest inventory plots and for the sample of the study area. Strong correlations were observed between estimates of AGB (r 0.88). The structural changes identified in the outlined crowns did not influence the values obtained for the sample area, which presented a reduction pattern (5.64%). Despite the negative changes that occurred in this study, no significant difference (p 0.05; Tukey test) of AGB was found among the evaluated period. The LiDAR technology has great potential for detecting large- scale changes and it is possible to obtain accurate environmental information (AGB). The approach used in the study may contribute for further analyses aimed at evaluating changes in AGB stock.
publishDate 2020
dc.date.none.fl_str_mv 2020-04-23
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.ufrj.br/index.php/aigeo/article/view/34207
10.11137/2020_1_228_238
url https://revistas.ufrj.br/index.php/aigeo/article/view/34207
identifier_str_mv 10.11137/2020_1_228_238
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/34207/19123
dc.rights.driver.fl_str_mv Copyright (c) 2020 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
dc.source.none.fl_str_mv Anuário do Instituto de Geociências; Vol 43, No 1 (2020); 228-238
Anuário do Instituto de Geociências; Vol 43, No 1 (2020); 228-238
1982-3908
0101-9759
reponame:Anuário do Instituto de Geociências (Online)
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 Anuário do Instituto de Geociências (Online)
collection Anuário do Instituto de Geociências (Online)
repository.name.fl_str_mv Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)
repository.mail.fl_str_mv anuario@igeo.ufrj.br||
_version_ 1797053545050013696