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: | Floresta e Ambiente |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300127 |
Resumo: | ABSTRACT 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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Floresta e Ambiente |
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Remote Sensing and Geostatistics Applied to Post-stratification of Eucalyptus Standsforest inventorykrigingNDVIABSTRACT 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%).Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300127Floresta e Ambiente v.25 n.3 2018reponame:Floresta e Ambienteinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ10.1590/2179-8087.058616info:eu-repo/semantics/openAccessOliveira,Ivy Mayara Sanches deSilveira,Eduarda Martiniano de OliveiraPaiva,Lara deAcerbi Júnior,Fausto WeimarMello,José Marcio deeng2018-07-27T00:00:00Zoai:scielo:S2179-80872018000300127Revistahttps://www.floram.org/PUBhttps://old.scielo.br/oai/scielo-oai.phpfloramjournal@gmail.com||floram@ufrrj.br||2179-80871415-0980opendoar:2018-07-27T00:00Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)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 NDVI |
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 NDVI |
topic |
forest inventory kriging NDVI |
description |
ABSTRACT 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 |
2018-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300127 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300127 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2179-8087.058616 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro |
publisher.none.fl_str_mv |
Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro |
dc.source.none.fl_str_mv |
Floresta e Ambiente v.25 n.3 2018 reponame:Floresta e Ambiente instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
institution |
UFRJ |
reponame_str |
Floresta e Ambiente |
collection |
Floresta e Ambiente |
repository.name.fl_str_mv |
Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ) |
repository.mail.fl_str_mv |
floramjournal@gmail.com||floram@ufrrj.br|| |
_version_ |
1750128142366801920 |