PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Cerne (Online) |
Texto Completo: | https://cerne.ufla.br/site/index.php/CERNE/article/view/1061 |
Resumo: | In the Gypsum Pole of Araripe, semiarid zone of Pernambuco, where is produces 97% of the plaster consumed in Brazil, a forest experiment with 1875 eucalyptus was cut off and all the trees were rigorously cubed by the Smalian method. The location of each tree was marked on a Cartesian plane, and a sample of 200 trees was removed by entirely random process. In the 200 sample trees, three estimation methods for variable volume timber, regression analysis, kriging and cokriging were used. To cokriging method, the secondary variable was the DBH (Diameter at Breast Height), and for the regression model of Spurr or the combined variable, it uses two explanatory variables: total height of the tree (H) and the DBH. The variables volume and DBH showed spatial dependency. To compare de methods it was used the coefficient of determination (R2) and the residual distribution of the errors (real x estimated data). The best results were achieved with the Spurr equation R2 = 0.82 and total volume estimated 166.25 m3. The cokriging provided and R2 = 0.72 with total volume estimated of 164.14 m3 and kriging had R2 = 0.32 and the total volume estimated of 163.21 m3. The real volume of the experiment was 166.14 m3. |
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PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSIONForest inventoryVolume of timberGeostatistics.In the Gypsum Pole of Araripe, semiarid zone of Pernambuco, where is produces 97% of the plaster consumed in Brazil, a forest experiment with 1875 eucalyptus was cut off and all the trees were rigorously cubed by the Smalian method. The location of each tree was marked on a Cartesian plane, and a sample of 200 trees was removed by entirely random process. In the 200 sample trees, three estimation methods for variable volume timber, regression analysis, kriging and cokriging were used. To cokriging method, the secondary variable was the DBH (Diameter at Breast Height), and for the regression model of Spurr or the combined variable, it uses two explanatory variables: total height of the tree (H) and the DBH. The variables volume and DBH showed spatial dependency. To compare de methods it was used the coefficient of determination (R2) and the residual distribution of the errors (real x estimated data). The best results were achieved with the Spurr equation R2 = 0.82 and total volume estimated 166.25 m3. The cokriging provided and R2 = 0.72 with total volume estimated of 164.14 m3 and kriging had R2 = 0.32 and the total volume estimated of 163.21 m3. The real volume of the experiment was 166.14 m3. CERNECERNE2016-04-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/1061CERNE; Vol. 21 No. 2 (2015); 243-250CERNE; v. 21 n. 2 (2015); 243-2502317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/1061/832Copyright (c) 2016 CERNEinfo:eu-repo/semantics/openAccessLundgren, Wellington Jorge CavalcantiSilva, José Antônio Aleixo daFerreira, Rinaldo Luiz Caraciolo2016-04-20T10:37:29Zoai:cerne.ufla.br:article/1061Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:21.981839Cerne (Online) - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
title |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
spellingShingle |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION Lundgren, Wellington Jorge Cavalcanti Forest inventory Volume of timber Geostatistics. |
title_short |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
title_full |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
title_fullStr |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
title_full_unstemmed |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
title_sort |
PREDICTIONG OF EUCALYPTUS WOOD BY COKRIGING, KRIGING AND REGRESSION |
author |
Lundgren, Wellington Jorge Cavalcanti |
author_facet |
Lundgren, Wellington Jorge Cavalcanti Silva, José Antônio Aleixo da Ferreira, Rinaldo Luiz Caraciolo |
author_role |
author |
author2 |
Silva, José Antônio Aleixo da Ferreira, Rinaldo Luiz Caraciolo |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Lundgren, Wellington Jorge Cavalcanti Silva, José Antônio Aleixo da Ferreira, Rinaldo Luiz Caraciolo |
dc.subject.por.fl_str_mv |
Forest inventory Volume of timber Geostatistics. |
topic |
Forest inventory Volume of timber Geostatistics. |
description |
In the Gypsum Pole of Araripe, semiarid zone of Pernambuco, where is produces 97% of the plaster consumed in Brazil, a forest experiment with 1875 eucalyptus was cut off and all the trees were rigorously cubed by the Smalian method. The location of each tree was marked on a Cartesian plane, and a sample of 200 trees was removed by entirely random process. In the 200 sample trees, three estimation methods for variable volume timber, regression analysis, kriging and cokriging were used. To cokriging method, the secondary variable was the DBH (Diameter at Breast Height), and for the regression model of Spurr or the combined variable, it uses two explanatory variables: total height of the tree (H) and the DBH. The variables volume and DBH showed spatial dependency. To compare de methods it was used the coefficient of determination (R2) and the residual distribution of the errors (real x estimated data). The best results were achieved with the Spurr equation R2 = 0.82 and total volume estimated 166.25 m3. The cokriging provided and R2 = 0.72 with total volume estimated of 164.14 m3 and kriging had R2 = 0.32 and the total volume estimated of 163.21 m3. The real volume of the experiment was 166.14 m3. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-04-07 |
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/1061 |
url |
https://cerne.ufla.br/site/index.php/CERNE/article/view/1061 |
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/1061/832 |
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. 2 (2015); 243-250 CERNE; v. 21 n. 2 (2015); 243-250 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 |
_version_ |
1799874942785814528 |