SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS

Detalhes bibliográficos
Autor(a) principal: Augustynczik, Andrey Lessa Derci
Data de Publicação: 2016
Outros Autores: Arce, Julio Eduardo, Silva, Arinei Carlos Lindbeck da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/1115
Resumo: One of the biggest challenges that forest managers face in forest planning is related to logistic issues of forest harvesting. The operational planning of forest harvesting must consider simultaneously the economic and environmental concerns, searching for increasing the efficiency and mitigating environmental damage related to the opening of forest cover. The inclusion of spatial aspects in forest harvesting is usually done through adjacency constraints. The main approaches to solve this sort of problem are ARM (Area restriction Model) and URM (Unit Restriction Model) models. In this context, the objective of this study was to perform the optimized forest planning of 236 stands of a Pinus taeda and Eucalyptus sp. forest, incorporating classical constraints like available area, timber flow, among others, and ARM and URM constraints, evaluating their effects on the optimization results. With the optimization outcomes, it is possible to conclude that ARM and URM model approaches are viable alternatives for solving forest harvest scheduling problems, being the ARM approach most suited for our case study, due to the possibility of higher profitability, while respecting maximum harvesting areas.
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spelling SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREASForest harvestingmaximum area constraintsforest planning.One of the biggest challenges that forest managers face in forest planning is related to logistic issues of forest harvesting. The operational planning of forest harvesting must consider simultaneously the economic and environmental concerns, searching for increasing the efficiency and mitigating environmental damage related to the opening of forest cover. The inclusion of spatial aspects in forest harvesting is usually done through adjacency constraints. The main approaches to solve this sort of problem are ARM (Area restriction Model) and URM (Unit Restriction Model) models. In this context, the objective of this study was to perform the optimized forest planning of 236 stands of a Pinus taeda and Eucalyptus sp. forest, incorporating classical constraints like available area, timber flow, among others, and ARM and URM constraints, evaluating their effects on the optimization results. With the optimization outcomes, it is possible to conclude that ARM and URM model approaches are viable alternatives for solving forest harvest scheduling problems, being the ARM approach most suited for our case study, due to the possibility of higher profitability, while respecting maximum harvesting areas.CERNECERNE2016-04-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/1115CERNE; Vol. 21 No. 4 (2015); 649-656CERNE; v. 21 n. 4 (2015); 649-6562317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/1115/876Copyright (c) 2016 CERNEinfo:eu-repo/semantics/openAccessAugustynczik, Andrey Lessa DerciArce, Julio EduardoSilva, Arinei Carlos Lindbeck da2016-04-19T15:00:16Zoai:cerne.ufla.br:article/1115Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:25.372522Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
title SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
spellingShingle SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
Augustynczik, Andrey Lessa Derci
Forest harvesting
maximum area constraints
forest planning.
title_short SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
title_full SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
title_fullStr SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
title_full_unstemmed SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
title_sort SPATIAL FOREST HARVEST PLANNING CONSIDERING MAXIMUM OPERATIONAL AREAS
author Augustynczik, Andrey Lessa Derci
author_facet Augustynczik, Andrey Lessa Derci
Arce, Julio Eduardo
Silva, Arinei Carlos Lindbeck da
author_role author
author2 Arce, Julio Eduardo
Silva, Arinei Carlos Lindbeck da
author2_role author
author
dc.contributor.author.fl_str_mv Augustynczik, Andrey Lessa Derci
Arce, Julio Eduardo
Silva, Arinei Carlos Lindbeck da
dc.subject.por.fl_str_mv Forest harvesting
maximum area constraints
forest planning.
topic Forest harvesting
maximum area constraints
forest planning.
description One of the biggest challenges that forest managers face in forest planning is related to logistic issues of forest harvesting. The operational planning of forest harvesting must consider simultaneously the economic and environmental concerns, searching for increasing the efficiency and mitigating environmental damage related to the opening of forest cover. The inclusion of spatial aspects in forest harvesting is usually done through adjacency constraints. The main approaches to solve this sort of problem are ARM (Area restriction Model) and URM (Unit Restriction Model) models. In this context, the objective of this study was to perform the optimized forest planning of 236 stands of a Pinus taeda and Eucalyptus sp. forest, incorporating classical constraints like available area, timber flow, among others, and ARM and URM constraints, evaluating their effects on the optimization results. With the optimization outcomes, it is possible to conclude that ARM and URM model approaches are viable alternatives for solving forest harvest scheduling problems, being the ARM approach most suited for our case study, due to the possibility of higher profitability, while respecting maximum harvesting areas.
publishDate 2016
dc.date.none.fl_str_mv 2016-04-19
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://cerne.ufla.br/site/index.php/CERNE/article/view/1115
url https://cerne.ufla.br/site/index.php/CERNE/article/view/1115
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/1115/876
dc.rights.driver.fl_str_mv Copyright (c) 2016 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 CERNE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol. 21 No. 4 (2015); 649-656
CERNE; v. 21 n. 4 (2015); 649-656
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
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