Remote sensing and geostatistics applied to post-stratification of eucalyptus stands
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/33430 |
Resumo: | Brazil has many rural properties with unmanaged eucalyptus stands. These plantations are heterogeneous, presenting different tree sizes, advanced ages, and large wood volumes that can be quantified using forest inventories. The prediction error of dendrometric variables, mainly in highly heterogeneous areas, can be associated with inadequate forest inventory procedures, i.e. low intensity of sampling plots. However, a larger number of plots increases the cost of inventorying. Therefore, a promising alternative is forest stratification into homogeneous sub areas. Accordingly, the aim of this study was to analyze the reduction of volume estimate errors by post-stratification procedures. We used the normalized difference vegetation index (NDVI) derived from Landsat 8 and Spot 6 images and geostatistical techniques, such as kriging the volume (V) and diameter at breast height (DBH). The most precise method to estimate the total volume was the stratified random sampling (STS), based on geostatistical interpolation, using the DBH (error lower than 10%). |
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Remote sensing and geostatistics applied to post-stratification of eucalyptus standsForest inventoryKrigingNormalized difference vegetation indexInventário florestalKrigagemÍndice de vegetação de diferença normalizadoBrazil has many rural properties with unmanaged eucalyptus stands. These plantations are heterogeneous, presenting different tree sizes, advanced ages, and large wood volumes that can be quantified using forest inventories. The prediction error of dendrometric variables, mainly in highly heterogeneous areas, can be associated with inadequate forest inventory procedures, i.e. low intensity of sampling plots. However, a larger number of plots increases the cost of inventorying. Therefore, a promising alternative is forest stratification into homogeneous sub areas. Accordingly, the aim of this study was to analyze the reduction of volume estimate errors by post-stratification procedures. We used the normalized difference vegetation index (NDVI) derived from Landsat 8 and Spot 6 images and geostatistical techniques, such as kriging the volume (V) and diameter at breast height (DBH). The most precise method to estimate the total volume was the stratified random sampling (STS), based on geostatistical interpolation, using the DBH (error lower than 10%).FLORAM2019-04-01T17:15:56Z2019-04-01T17:15:56Z2018info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfOLIVEIRA, I. M. S. de et al. Remote sensing and geostatistics applied to post-stratification of eucalyptus stands. Floresta e Ambiente, Seropédica, v. 25, n. 3, p. 1-11, 2018. DOI: http://dx.doi.org/10.1590/2179-8087.058616.http://repositorio.ufla.br/jspui/handle/1/33430Floresta e Ambientereponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessOliveira, Ivy Mayara Sanches deSilveira, Eduarda Martiniano de OliveiraPaiva, Lara deAcerbi Júnior, Fausto WeimarMello, José Marcio deeng2019-04-01T17:15:56Zoai:localhost:1/33430Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2019-04-01T17:15:56Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
title |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
spellingShingle |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands Oliveira, Ivy Mayara Sanches de Forest inventory Kriging Normalized difference vegetation index Inventário florestal Krigagem Índice de vegetação de diferença normalizado |
title_short |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
title_full |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
title_fullStr |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
title_full_unstemmed |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
title_sort |
Remote sensing and geostatistics applied to post-stratification of eucalyptus stands |
author |
Oliveira, Ivy Mayara Sanches de |
author_facet |
Oliveira, Ivy Mayara Sanches de Silveira, Eduarda Martiniano de Oliveira Paiva, Lara de Acerbi Júnior, Fausto Weimar Mello, José Marcio de |
author_role |
author |
author2 |
Silveira, Eduarda Martiniano de Oliveira Paiva, Lara de Acerbi Júnior, Fausto Weimar Mello, José Marcio de |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Oliveira, Ivy Mayara Sanches de Silveira, Eduarda Martiniano de Oliveira Paiva, Lara de Acerbi Júnior, Fausto Weimar Mello, José Marcio de |
dc.subject.por.fl_str_mv |
Forest inventory Kriging Normalized difference vegetation index Inventário florestal Krigagem Índice de vegetação de diferença normalizado |
topic |
Forest inventory Kriging Normalized difference vegetation index Inventário florestal Krigagem Índice de vegetação de diferença normalizado |
description |
Brazil has many rural properties with unmanaged eucalyptus stands. These plantations are heterogeneous, presenting different tree sizes, advanced ages, and large wood volumes that can be quantified using forest inventories. The prediction error of dendrometric variables, mainly in highly heterogeneous areas, can be associated with inadequate forest inventory procedures, i.e. low intensity of sampling plots. However, a larger number of plots increases the cost of inventorying. Therefore, a promising alternative is forest stratification into homogeneous sub areas. Accordingly, the aim of this study was to analyze the reduction of volume estimate errors by post-stratification procedures. We used the normalized difference vegetation index (NDVI) derived from Landsat 8 and Spot 6 images and geostatistical techniques, such as kriging the volume (V) and diameter at breast height (DBH). The most precise method to estimate the total volume was the stratified random sampling (STS), based on geostatistical interpolation, using the DBH (error lower than 10%). |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 2019-04-01T17:15:56Z 2019-04-01T17:15:56Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
OLIVEIRA, I. M. S. de et al. Remote sensing and geostatistics applied to post-stratification of eucalyptus stands. Floresta e Ambiente, Seropédica, v. 25, n. 3, p. 1-11, 2018. DOI: http://dx.doi.org/10.1590/2179-8087.058616. http://repositorio.ufla.br/jspui/handle/1/33430 |
identifier_str_mv |
OLIVEIRA, I. M. S. de et al. Remote sensing and geostatistics applied to post-stratification of eucalyptus stands. Floresta e Ambiente, Seropédica, v. 25, n. 3, p. 1-11, 2018. DOI: http://dx.doi.org/10.1590/2179-8087.058616. |
url |
http://repositorio.ufla.br/jspui/handle/1/33430 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
FLORAM |
publisher.none.fl_str_mv |
FLORAM |
dc.source.none.fl_str_mv |
Floresta e Ambiente 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 |
_version_ |
1807835085686177792 |