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: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/14208
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 analysisEstimativa subpixel da cobertura arbórea e superfície exposta utilizando análise por árvore de regressãoRemote sensingMappingCerradoSensoriamento remotoMapeamentoSub-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. A análise subpixel é capaz de gerar campos contínuos que representam a variabilidade intrínseca das classes temáticas. Neste trabalho, objetivou-se desenvolver um modelo numérico para representar a variabilidade de cobertura de dossel e de superfície exposta dentro de cada formação florestal. Este estudo foi conduzido em área de amortecimento ao longo da sub-bacia no médio São Francisco em MG, Brasil. Foram usados imagens dos satélites Landsat TM, e IKONOS, e o algoritmo GUIDE para ajustes dos modelos. Os resultados foram duas imagens índices, uma de cobertura arbórea e outra de superfície exposta para toda a área estudada, utilizando o modelo de árvore de regressão. O uso de modelos não-paramétricos e não-lineares por árvore de regressão apresentou resultados satisfatórios na representação de padrões de formações florestais aluviais, deciduais e savânicas.Universidade Federal de Lavras (UFLA)2015-05-122017-08-01T20:13:54Z2017-08-01T20:13:54Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfTONELI, C. A. Z.; CARVALHO, L. M. T. de. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis. CERNE, Lavras, v. 17, n. 3, p. 411-416, jul./set. 2011.http://repositorio.ufla.br/jspui/handle/1/142082317-63420104-7760reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttp://www.cerne.ufla.br/site/index.php/CERNE/article/view/63/54Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessToneli, Carlos Augusto ZangrandoCarvalho, Luís Marcelo Tavares de2021-06-23T00:04:39Zoai:localhost:1/14208Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-06-23T00:04:39Repositório Institucional da UFLA - 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
Estimativa subpixel da cobertura arbórea e superfície exposta utilizando análise por árvore de regressão
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
Sensoriamento remoto
Mapeamento
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
Sensoriamento remoto
Mapeamento
topic Remote sensing
Mapping
Cerrado
Sensoriamento remoto
Mapeamento
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
2017-08-01T20:13:54Z
2017-08-01T20:13:54Z
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 TONELI, C. A. Z.; CARVALHO, L. M. T. de. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis. CERNE, Lavras, v. 17, n. 3, p. 411-416, jul./set. 2011.
http://repositorio.ufla.br/jspui/handle/1/14208
identifier_str_mv TONELI, C. A. Z.; CARVALHO, L. M. T. de. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis. CERNE, Lavras, v. 17, n. 3, p. 411-416, jul./set. 2011.
url http://repositorio.ufla.br/jspui/handle/1/14208
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.cerne.ufla.br/site/index.php/CERNE/article/view/63/54
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 Universidade Federal de Lavras (UFLA)
publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA)
dc.source.none.fl_str_mv 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
_version_ 1807835163128758272

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