SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS

Detalhes bibliográficos
Autor(a) principal: Toneli, Carlos Augusto Zangrando
Data de Publicação: 2015
Outros Autores: Carvalho, Luís Marcelo Tavares de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/63
Resumo: Sub-pixel analysis is capable of generating continuous fields, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation. 
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spelling SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSISRemote sensingmappingcerradoSub-pixel analysis is capable of generating continuous fields, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation. CERNECERNE2015-05-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/63CERNE; Vol. 17 No. 3 (2011); 411-416CERNE; v. 17 n. 3 (2011); 411-4162317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://cerne.ufla.br/site/index.php/CERNE/article/view/63/54Copyright (c) 2015 Carlos Augusto Zangrando Toneli, Luís Marcelo Tavares de Carvalhoinfo:eu-repo/semantics/openAccessToneli, Carlos Augusto ZangrandoCarvalho, Luís Marcelo Tavares de2015-05-12T11:04:19Zoai:cerne.ufla.br:article/63Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-23T16:28:04.345126Cerne (Online) - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
title SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
spellingShingle SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
Toneli, Carlos Augusto Zangrando
Remote sensing
mapping
cerrado
title_short SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
title_full SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
title_fullStr SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
title_full_unstemmed SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
title_sort SUB-PIXEL ESTIMATION OF TREE COVER AND BARE SURFACE DENSITIES USING REGRESSION TREE ANALYSIS
author Toneli, Carlos Augusto Zangrando
author_facet Toneli, Carlos Augusto Zangrando
Carvalho, Luís Marcelo Tavares de
author_role author
author2 Carvalho, Luís Marcelo Tavares de
author2_role author
dc.contributor.author.fl_str_mv Toneli, Carlos Augusto Zangrando
Carvalho, Luís Marcelo Tavares de
dc.subject.por.fl_str_mv Remote sensing
mapping
cerrado
topic Remote sensing
mapping
cerrado
description Sub-pixel analysis is capable of generating continuous fields, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation. 
publishDate 2015
dc.date.none.fl_str_mv 2015-05-12
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/63
url https://cerne.ufla.br/site/index.php/CERNE/article/view/63
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/63/54
dc.rights.driver.fl_str_mv Copyright (c) 2015 Carlos Augusto Zangrando Toneli, Luís Marcelo Tavares de Carvalho
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Carlos Augusto Zangrando Toneli, Luís Marcelo Tavares de Carvalho
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. 17 No. 3 (2011); 411-416
CERNE; v. 17 n. 3 (2011); 411-416
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
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