THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS

Detalhes bibliográficos
Autor(a) principal: Silveira, Eduarda Martiniano de Oliveira
Data de Publicação: 2015
Outros Autores: Carvalho, Luis Marcelo Tavares de, Acerbi-Júnior, Fausto Weimar, Mello, José Marcio de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/643
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.
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spelling THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODISRemote sensingtime seriesvegetation indiesThe 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.CERNECERNE2015-10-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/643CERNE; Vol. 14 No. 2 (2008); 177-184CERNE; v. 14 n. 2 (2008); 177-1842317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/643/543Copyright (c) 2015 CERNEinfo:eu-repo/semantics/openAccessSilveira, Eduarda Martiniano de OliveiraCarvalho, Luis Marcelo Tavares deAcerbi-Júnior, Fausto WeimarMello, José Marcio de2015-10-29T17:06:47Zoai:cerne.ufla.br:article/643Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:02.506117Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
title THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
spellingShingle THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
Silveira, Eduarda Martiniano de Oliveira
Remote sensing
time series
vegetation indies
title_short THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
title_full THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
title_fullStr THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
title_full_unstemmed THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM MODIS
title_sort THE ASSESSMENT OF VEGETATION SEASONAL DYNAMICS USING MULTITEMPORAL NDVI AND EVI IMAGES DERIVED FORM 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
topic Remote sensing
time series
vegetation indies
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.
publishDate 2015
dc.date.none.fl_str_mv 2015-10-28
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/643
url https://cerne.ufla.br/site/index.php/CERNE/article/view/643
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/643/543
dc.rights.driver.fl_str_mv Copyright (c) 2015 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 CERNE
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. 14 No. 2 (2008); 177-184
CERNE; v. 14 n. 2 (2008); 177-184
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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