Dominant height projection model with the addition of environmental variables
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , , |
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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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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1815439010151006208 |