Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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. |
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Anuário do Instituto de Geociências (Online) |
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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|| |
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1797053545050013696 |