Dominant height projection model with the addition of environmental variables

Detalhes bibliográficos
Autor(a) principal: Filho, Antonio Carlos Ferraz
Data de Publicação: 2015
Outros Autores: Scolforo, José Roberto Soares, Ferreira, Maria Zélia, Maestri, Romualdo, Assis, Adriana Leandra de, Oliveira, Antonio Donizette de, Mello, José Márcio de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://www.cerne.ufla.br/site/index.php/CERNE/article/view/65
http://repositorio.ufla.br/jspui/handle/1/14628
Resumo: This study investigated the behavior of climatic variables inserted as inclination modifiers of the Chapman-Richards model for estimating dominant height. Thus, 1507 data pairs from a Continuous Forestry Inventory of clonal eucalyptus stands were used. The stands are located in the States of Espírito Santo and southern Bahia. The climatic variables were inserted in the dominant height model because the model is a key variable in the whole prognosis system. The models were adjusted using 1360 data pairs, where the rest of the data was reserved for model validation. The climatic variables were selected by using the Backward model construction method. The climatic variables indicated by the Backward method and inserted in the model were: mean monthly precipitation and solar radiation. The inclusion of climatic variables in the model resulted in a precision gain of 19.8% for dominant height projection values when compared with the conventional model. The advantage of the method used in this study is the actualization of inventory data contemplating climatic history and productivity estimates in areas without prior plantation. 
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spelling Dominant height projection model with the addition of environmental variablesModelo de projeção em altura dominante com adição de variáveis ambientaisClimatic variableProjection modelDominant heightVariáveis climáticasAltura dominanteModelo de projeçãoThis study investigated the behavior of climatic variables inserted as inclination modifiers of the Chapman-Richards model for estimating dominant height. Thus, 1507 data pairs from a Continuous Forestry Inventory of clonal eucalyptus stands were used. The stands are located in the States of Espírito Santo and southern Bahia. The climatic variables were inserted in the dominant height model because the model is a key variable in the whole prognosis system. The models were adjusted using 1360 data pairs, where the rest of the data was reserved for model validation. The climatic variables were selected by using the Backward model construction method. The climatic variables indicated by the Backward method and inserted in the model were: mean monthly precipitation and solar radiation. The inclusion of climatic variables in the model resulted in a precision gain of 19.8% for dominant height projection values when compared with the conventional model. The advantage of the method used in this study is the actualization of inventory data contemplating climatic history and productivity estimates in areas without prior plantation. Conduziu-se este estudo, com a fi nalidade de avaliar o efeito da introdução de variáveis ambientais introduzidas como modifi cadores da inclinação do modelo de Chapman-Richards, para a projeção de altura dominante. Para isso foram utilizados 1507 pares de dados de IFC provenientes de plantios clonais de eucalipto, localizados nos Estados do Espírito Santo e sul da Bahia. As variáveis ambientais foram introduzidas no modelo de altura dominante por ser essa variável chave em todo o sistema de prognose. O ajuste dos modelos foi realizado com 1360 pares de dados, sendo que o restante dos dados foram reservados para a validação do modelo. A escolha das variáveis ambientais foi feita pelo método de construção de modelos Backward. As variáveis ambientais indicadas pelo método Backward e inseridas no modelo de projeção foram: precipitação mensal média e radiação solar média. O ganho com a inclusão das variáveis climáticas na precisão das projeções da altura dominante foi de 19,8% em relação ao modelo sem variável ambiental. A metodologia de modelagem utilizada neste trabalho apresenta a vantagem de poder atualizar inventários com base no histórico climático e estimar produtividade em locais sem histórico de plantios.CERNE2015-05-122017-08-01T20:15:26Z2017-08-01T20:15:26Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://www.cerne.ufla.br/site/index.php/CERNE/article/view/65FERRAZ FILHO, A. C. et al. Dominant height projection model with the addition of environmental variables. Cerne, Lavras, v. 17, n. 3, p. 427-433, jul./set. 2011.http://repositorio.ufla.br/jspui/handle/1/14628CERNE; Vol 17 No 3 (2011); 427-433CERNE; Vol 17 No 3 (2011); 427-4332317-63420104-7760reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttp://www.cerne.ufla.br/site/index.php/CERNE/article/view/65/56Copyright (c) 2015 Antonio Carlos Ferraz Filho, José Roberto Soares Scolforo, Maria Zélia Ferreira, Romualdo Maestri, Adriana Leandra de Assis, Antonio Donizette de Oliveira, José Márcio de MelloAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFilho, Antonio Carlos FerrazScolforo, José Roberto SoaresFerreira, Maria ZéliaMaestri, RomualdoAssis, Adriana Leandra deOliveira, Antonio Donizette deMello, José Márcio de2021-04-07T18:37:43Zoai:localhost:1/14628Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-04-07T18:37:43Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Dominant height projection model with the addition of environmental variables
Modelo de projeção em altura dominante com adição de variáveis ambientais
title Dominant height projection model with the addition of environmental variables
spellingShingle Dominant height projection model with the addition of environmental variables
Filho, Antonio Carlos Ferraz
Climatic variable
Projection model
Dominant height
Variáveis climáticas
Altura dominante
Modelo de projeção
title_short Dominant height projection model with the addition of environmental variables
title_full Dominant height projection model with the addition of environmental variables
title_fullStr Dominant height projection model with the addition of environmental variables
title_full_unstemmed Dominant height projection model with the addition of environmental variables
title_sort Dominant height projection model with the addition of environmental variables
author Filho, Antonio Carlos Ferraz
author_facet Filho, Antonio Carlos Ferraz
Scolforo, José Roberto Soares
Ferreira, Maria Zélia
Maestri, Romualdo
Assis, Adriana Leandra de
Oliveira, Antonio Donizette de
Mello, José Márcio de
author_role author
author2 Scolforo, José Roberto Soares
Ferreira, Maria Zélia
Maestri, Romualdo
Assis, Adriana Leandra de
Oliveira, Antonio Donizette de
Mello, José Márcio de
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Filho, Antonio Carlos Ferraz
Scolforo, José Roberto Soares
Ferreira, Maria Zélia
Maestri, Romualdo
Assis, Adriana Leandra de
Oliveira, Antonio Donizette de
Mello, José Márcio de
dc.subject.por.fl_str_mv Climatic variable
Projection model
Dominant height
Variáveis climáticas
Altura dominante
Modelo de projeção
topic Climatic variable
Projection model
Dominant height
Variáveis climáticas
Altura dominante
Modelo de projeção
description This study investigated the behavior of climatic variables inserted as inclination modifiers of the Chapman-Richards model for estimating dominant height. Thus, 1507 data pairs from a Continuous Forestry Inventory of clonal eucalyptus stands were used. The stands are located in the States of Espírito Santo and southern Bahia. The climatic variables were inserted in the dominant height model because the model is a key variable in the whole prognosis system. The models were adjusted using 1360 data pairs, where the rest of the data was reserved for model validation. The climatic variables were selected by using the Backward model construction method. The climatic variables indicated by the Backward method and inserted in the model were: mean monthly precipitation and solar radiation. The inclusion of climatic variables in the model resulted in a precision gain of 19.8% for dominant height projection values when compared with the conventional model. The advantage of the method used in this study is the actualization of inventory data contemplating climatic history and productivity estimates in areas without prior plantation. 
publishDate 2015
dc.date.none.fl_str_mv 2015-05-12
2017-08-01T20:15:26Z
2017-08-01T20:15:26Z
2017-08-01
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 http://www.cerne.ufla.br/site/index.php/CERNE/article/view/65
FERRAZ FILHO, A. C. et al. Dominant height projection model with the addition of environmental variables. Cerne, Lavras, v. 17, n. 3, p. 427-433, jul./set. 2011.
http://repositorio.ufla.br/jspui/handle/1/14628
url http://www.cerne.ufla.br/site/index.php/CERNE/article/view/65
http://repositorio.ufla.br/jspui/handle/1/14628
identifier_str_mv FERRAZ FILHO, A. C. et al. Dominant height projection model with the addition of environmental variables. Cerne, Lavras, v. 17, n. 3, p. 427-433, jul./set. 2011.
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv http://www.cerne.ufla.br/site/index.php/CERNE/article/view/65/56
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv CERNE
publisher.none.fl_str_mv CERNE
dc.source.none.fl_str_mv CERNE; Vol 17 No 3 (2011); 427-433
CERNE; Vol 17 No 3 (2011); 427-433
2317-6342
0104-7760
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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