Measurement errors in forest inventories and comparison of biomass estimation methods

Detalhes bibliográficos
Autor(a) principal: Castelo,Adriano
Data de Publicação: 2018
Outros Autores: Guedes,Marcelino, Sotta,Eleneide, Blanc,Lilian
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://scielo.pt/scielo.php?script=sci_arttext&pid=S0871-018X2018000300030
Resumo: Accurate quantification of above-ground biomass (AGB) in managed forests requires: consideration of inventory errors and the use of local or large-scale allometric models. In this study we focus on the measurement errors, data collection errors and we compared different methods to estimate AGB in managed tropical forest. The data were collected in 15 plots of 100 x 100 m. We evaluated the errors of the forest inventory of 8.898 trees. We used four methods to estimate AGB: three methods which use a pan-tropical equation, which depends on wood density data, with different ways of integrating the wood density data (obtained from dataset of the Brazilian Forest Service, Jari and Global Wood Density Database - GWDD); and one local equation. The main inventory errors were: problems with the same tree being identified as a different tree in consecutive measurements (16% of the trees). AGB estimates using each of the four methods were significantly different.
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spelling Measurement errors in forest inventories and comparison of biomass estimation methodsrainforest managementforest inventory of companieslocal and pan-tropical allometric modelsAccurate quantification of above-ground biomass (AGB) in managed forests requires: consideration of inventory errors and the use of local or large-scale allometric models. In this study we focus on the measurement errors, data collection errors and we compared different methods to estimate AGB in managed tropical forest. The data were collected in 15 plots of 100 x 100 m. We evaluated the errors of the forest inventory of 8.898 trees. We used four methods to estimate AGB: three methods which use a pan-tropical equation, which depends on wood density data, with different ways of integrating the wood density data (obtained from dataset of the Brazilian Forest Service, Jari and Global Wood Density Database - GWDD); and one local equation. The main inventory errors were: problems with the same tree being identified as a different tree in consecutive measurements (16% of the trees). AGB estimates using each of the four methods were significantly different.Sociedade de Ciências Agrárias de Portugal2018-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articletext/htmlhttp://scielo.pt/scielo.php?script=sci_arttext&pid=S0871-018X2018000300030Revista de Ciências Agrárias v.41 n.3 2018reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttp://scielo.pt/scielo.php?script=sci_arttext&pid=S0871-018X2018000300030Castelo,AdrianoGuedes,MarcelinoSotta,EleneideBlanc,Lilianinfo:eu-repo/semantics/openAccess2024-02-06T17:02:35Zoai:scielo:S0871-018X2018000300030Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:17:35.450110Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Measurement errors in forest inventories and comparison of biomass estimation methods
title Measurement errors in forest inventories and comparison of biomass estimation methods
spellingShingle Measurement errors in forest inventories and comparison of biomass estimation methods
Castelo,Adriano
rainforest management
forest inventory of companies
local and pan-tropical allometric models
title_short Measurement errors in forest inventories and comparison of biomass estimation methods
title_full Measurement errors in forest inventories and comparison of biomass estimation methods
title_fullStr Measurement errors in forest inventories and comparison of biomass estimation methods
title_full_unstemmed Measurement errors in forest inventories and comparison of biomass estimation methods
title_sort Measurement errors in forest inventories and comparison of biomass estimation methods
author Castelo,Adriano
author_facet Castelo,Adriano
Guedes,Marcelino
Sotta,Eleneide
Blanc,Lilian
author_role author
author2 Guedes,Marcelino
Sotta,Eleneide
Blanc,Lilian
author2_role author
author
author
dc.contributor.author.fl_str_mv Castelo,Adriano
Guedes,Marcelino
Sotta,Eleneide
Blanc,Lilian
dc.subject.por.fl_str_mv rainforest management
forest inventory of companies
local and pan-tropical allometric models
topic rainforest management
forest inventory of companies
local and pan-tropical allometric models
description Accurate quantification of above-ground biomass (AGB) in managed forests requires: consideration of inventory errors and the use of local or large-scale allometric models. In this study we focus on the measurement errors, data collection errors and we compared different methods to estimate AGB in managed tropical forest. The data were collected in 15 plots of 100 x 100 m. We evaluated the errors of the forest inventory of 8.898 trees. We used four methods to estimate AGB: three methods which use a pan-tropical equation, which depends on wood density data, with different ways of integrating the wood density data (obtained from dataset of the Brazilian Forest Service, Jari and Global Wood Density Database - GWDD); and one local equation. The main inventory errors were: problems with the same tree being identified as a different tree in consecutive measurements (16% of the trees). AGB estimates using each of the four methods were significantly different.
publishDate 2018
dc.date.none.fl_str_mv 2018-09-01
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dc.identifier.uri.fl_str_mv http://scielo.pt/scielo.php?script=sci_arttext&pid=S0871-018X2018000300030
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dc.language.iso.fl_str_mv eng
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dc.publisher.none.fl_str_mv Sociedade de Ciências Agrárias de Portugal
publisher.none.fl_str_mv Sociedade de Ciências Agrárias de Portugal
dc.source.none.fl_str_mv Revista de Ciências Agrárias v.41 n.3 2018
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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