The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS

Detalhes bibliográficos
Autor(a) principal: Silveira, Eduarda Martiniano de Oliveira
Data de Publicação: 2008
Outros Autores: Carvalho, Luis Marcelo Tavares de, Acerbi-Júnior, Fausto Weimar, Mello, José Marcio de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/12019
Resumo: The objectives of this work were to characterize seasonal dynamics of cerrado, deciduous and semideciduous forests in the north of Minas Gerais, Brazil. Time series of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS sensor, were compared by analyzing temporal profiles and image classification results. The results showed that: (1) there is an agreement between vegetation indexes and the monthly precipitation pattern; (2) deciduous forest showed the lowest values and the highest variation; (3) cerrado and the semideciduous forest presented higher values and lower variation; (4) based on the classification accuracies the best vegetation index for mapping the vegetation classes in the study area was the NDVI, however both indexes might be used to assess the vegetation seasonal dynamic; and (5) further research need to be carried out exploring the use of feature extractions algorithms to improve classification accuracy of cerrado, semideciduous and deciduos forests in Minas Gerais, Brazil. Key words: Remote sensi
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spelling The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODISCaracterização da dinâmica sazonal da vegetação usando imagens multitemporais NDVI e EVI derivadas do sensor MODISRemote sensingTime seriesVegetation indiesSensoriamento remotoSérie multitemporalÍndices de vegetaçãoThe objectives of this work were to characterize seasonal dynamics of cerrado, deciduous and semideciduous forests in the north of Minas Gerais, Brazil. Time series of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS sensor, were compared by analyzing temporal profiles and image classification results. The results showed that: (1) there is an agreement between vegetation indexes and the monthly precipitation pattern; (2) deciduous forest showed the lowest values and the highest variation; (3) cerrado and the semideciduous forest presented higher values and lower variation; (4) based on the classification accuracies the best vegetation index for mapping the vegetation classes in the study area was the NDVI, however both indexes might be used to assess the vegetation seasonal dynamic; and (5) further research need to be carried out exploring the use of feature extractions algorithms to improve classification accuracy of cerrado, semideciduous and deciduos forests in Minas Gerais, Brazil. Key words: Remote sensiO objetivo deste trabalho foi caracterizar a dinâmica sazonal do cerrado, floresta estacional semidecidual e decidual no norte do estado de Minas Gerais, Brasil. Séries multitemporais dos índices de vegetação NDVI (índice de vegetação da diferença normalizada) e EVI (índice de vegetação melhorado) derivados do sensor MODIS, foram comparadas analisando o perfil temporal e os resultados de classificação das imagens. Os resultados mostraram que: (1) Os índices de vegetação estudados refletiram o padrão sazonal das fisionomias, diferenciando os períodos chuvosos e os períodos de seca; (2) a fisionomia floresta estacional decidual apresentou menores valores dos índices e maior variação; (3) as fisionomias cerrado e floresta estacional semidecidual apresentaram alto valores dos índices e baixa variação; (4) de acordo com os resultados das classificações o melhor índice para o mapeamento das fisionomias na área de estudo foi o NDVI, porém ambos podem ser usados para avaliar a dinâmica sazonal da vegetação; e (5) estudos precisam ser realizados explorando algoritmos de extração de feições para melhorar a acuracidade do mapeamento das fisionomias cerrado, floresta decídua e semidecidua na área de estudo.Universidade Federal de Lavras2016-11-28T12:57:04Z2016-11-28T12:57:04Z2008info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSILVEIRA, E. M. de O. et al. The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS. Cerne, Lavras, v. 14, n. 2, p. 177-184, abr./jun. 2008.http://repositorio.ufla.br/jspui/handle/1/12019Cernereponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLASilveira, Eduarda Martiniano de OliveiraCarvalho, Luis Marcelo Tavares deAcerbi-Júnior, Fausto WeimarMello, José Marcio deinfo:eu-repo/semantics/openAccesseng2016-11-28T13:10:21Zoai:localhost:1/12019Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2016-11-28T13:10:21Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
Caracterização da dinâmica sazonal da vegetação usando imagens multitemporais NDVI e EVI derivadas do sensor MODIS
title The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
spellingShingle The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
Silveira, Eduarda Martiniano de Oliveira
Remote sensing
Time series
Vegetation indies
Sensoriamento remoto
Série multitemporal
Índices de vegetação
title_short The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
title_full The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
title_fullStr The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
title_full_unstemmed The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
title_sort The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS
author Silveira, Eduarda Martiniano de Oliveira
author_facet Silveira, Eduarda Martiniano de Oliveira
Carvalho, Luis Marcelo Tavares de
Acerbi-Júnior, Fausto Weimar
Mello, José Marcio de
author_role author
author2 Carvalho, Luis Marcelo Tavares de
Acerbi-Júnior, Fausto Weimar
Mello, José Marcio de
author2_role author
author
author
dc.contributor.author.fl_str_mv Silveira, Eduarda Martiniano de Oliveira
Carvalho, Luis Marcelo Tavares de
Acerbi-Júnior, Fausto Weimar
Mello, José Marcio de
dc.subject.por.fl_str_mv Remote sensing
Time series
Vegetation indies
Sensoriamento remoto
Série multitemporal
Índices de vegetação
topic Remote sensing
Time series
Vegetation indies
Sensoriamento remoto
Série multitemporal
Índices de vegetação
description The objectives of this work were to characterize seasonal dynamics of cerrado, deciduous and semideciduous forests in the north of Minas Gerais, Brazil. Time series of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS sensor, were compared by analyzing temporal profiles and image classification results. The results showed that: (1) there is an agreement between vegetation indexes and the monthly precipitation pattern; (2) deciduous forest showed the lowest values and the highest variation; (3) cerrado and the semideciduous forest presented higher values and lower variation; (4) based on the classification accuracies the best vegetation index for mapping the vegetation classes in the study area was the NDVI, however both indexes might be used to assess the vegetation seasonal dynamic; and (5) further research need to be carried out exploring the use of feature extractions algorithms to improve classification accuracy of cerrado, semideciduous and deciduos forests in Minas Gerais, Brazil. Key words: Remote sensi
publishDate 2008
dc.date.none.fl_str_mv 2008
2016-11-28T12:57:04Z
2016-11-28T12:57:04Z
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 SILVEIRA, E. M. de O. et al. The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS. Cerne, Lavras, v. 14, n. 2, p. 177-184, abr./jun. 2008.
http://repositorio.ufla.br/jspui/handle/1/12019
identifier_str_mv SILVEIRA, E. M. de O. et al. The assessment of vegetation seasonal dynamics using multitemporal NDVI and EVI images derived from MODIS. Cerne, Lavras, v. 14, n. 2, p. 177-184, abr./jun. 2008.
url http://repositorio.ufla.br/jspui/handle/1/12019
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv Cerne
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
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