Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets

Detalhes bibliográficos
Autor(a) principal: CORDEIRO,ANA PAULA A.
Data de Publicação: 2021
Outros Autores: ALVES,RITA DE CÁSSIA M., STEFFLER,ANA PAULA L.W., MENGUE,VAGNER P., FONTANA,DENISE C., ROGLIO,VINICIUS S., GUASSELLI,LAURINDO A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000501006
Resumo: Abstract This study aimed to classify the homogeneous regions of vegetation cover, which occur in Rio Grande do Sul, formed by clustering of pixels with same pattern of temporal variability of the Normalized Difference Vegetation Index (NDVI) of AVHRR GIMMS and MODIS series and to compare their temporal dynamics. We use K means cluster analysis for defining homogeneous regions, based on the temporal variability of GIMMS (8 km spatial resolution) and MODIS (1 km spatial resolution) NDVI data sets, using monthly images mean from 2000 to 2008 (overlapping period); and we analyzed the annual pattern of NDVI. Accuracy assessment was done with Landsat images. The results show that the temporal variability of GIMMS and MODIS NDVI allows to delimit similar homogeneous regions in order to mapping the main vegetation cover. MODIS series shows a greater detail in the definition of the regions, but with compatibility with those generated by GIMMS. The temporal dynamics show a typical seasonal pattern, with variations of NDVI amplitude between the groups, that allow to monitor phenological changes. The deviations from calibration between times series are linear, which would facilitate a correction in order to construct a long synthetic time series for studies of land cover change.
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spelling Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data setsagricultureclassificationclusteringforestgrasslandkmeansAbstract This study aimed to classify the homogeneous regions of vegetation cover, which occur in Rio Grande do Sul, formed by clustering of pixels with same pattern of temporal variability of the Normalized Difference Vegetation Index (NDVI) of AVHRR GIMMS and MODIS series and to compare their temporal dynamics. We use K means cluster analysis for defining homogeneous regions, based on the temporal variability of GIMMS (8 km spatial resolution) and MODIS (1 km spatial resolution) NDVI data sets, using monthly images mean from 2000 to 2008 (overlapping period); and we analyzed the annual pattern of NDVI. Accuracy assessment was done with Landsat images. The results show that the temporal variability of GIMMS and MODIS NDVI allows to delimit similar homogeneous regions in order to mapping the main vegetation cover. MODIS series shows a greater detail in the definition of the regions, but with compatibility with those generated by GIMMS. The temporal dynamics show a typical seasonal pattern, with variations of NDVI amplitude between the groups, that allow to monitor phenological changes. The deviations from calibration between times series are linear, which would facilitate a correction in order to construct a long synthetic time series for studies of land cover change.Academia Brasileira de Ciências2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000501006Anais da Academia Brasileira de Ciências v.93 n.3 2021reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202120201278info:eu-repo/semantics/openAccessCORDEIRO,ANA PAULA A.ALVES,RITA DE CÁSSIA M.STEFFLER,ANA PAULA L.W.MENGUE,VAGNER P.FONTANA,DENISE C.ROGLIO,VINICIUS S.GUASSELLI,LAURINDO A.eng2021-06-11T00:00:00Zoai:scielo:S0001-37652021000501006Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2021-06-11T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
title Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
spellingShingle Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
CORDEIRO,ANA PAULA A.
agriculture
classification
clustering
forest
grassland
kmeans
title_short Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
title_full Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
title_fullStr Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
title_full_unstemmed Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
title_sort Classification of homogeneous regions of vegetation cover in the State of Rio Grande do Sul, Brazil and its temporal dynamics, using AVHRR GIMMS and MODIS data sets
author CORDEIRO,ANA PAULA A.
author_facet CORDEIRO,ANA PAULA A.
ALVES,RITA DE CÁSSIA M.
STEFFLER,ANA PAULA L.W.
MENGUE,VAGNER P.
FONTANA,DENISE C.
ROGLIO,VINICIUS S.
GUASSELLI,LAURINDO A.
author_role author
author2 ALVES,RITA DE CÁSSIA M.
STEFFLER,ANA PAULA L.W.
MENGUE,VAGNER P.
FONTANA,DENISE C.
ROGLIO,VINICIUS S.
GUASSELLI,LAURINDO A.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv CORDEIRO,ANA PAULA A.
ALVES,RITA DE CÁSSIA M.
STEFFLER,ANA PAULA L.W.
MENGUE,VAGNER P.
FONTANA,DENISE C.
ROGLIO,VINICIUS S.
GUASSELLI,LAURINDO A.
dc.subject.por.fl_str_mv agriculture
classification
clustering
forest
grassland
kmeans
topic agriculture
classification
clustering
forest
grassland
kmeans
description Abstract This study aimed to classify the homogeneous regions of vegetation cover, which occur in Rio Grande do Sul, formed by clustering of pixels with same pattern of temporal variability of the Normalized Difference Vegetation Index (NDVI) of AVHRR GIMMS and MODIS series and to compare their temporal dynamics. We use K means cluster analysis for defining homogeneous regions, based on the temporal variability of GIMMS (8 km spatial resolution) and MODIS (1 km spatial resolution) NDVI data sets, using monthly images mean from 2000 to 2008 (overlapping period); and we analyzed the annual pattern of NDVI. Accuracy assessment was done with Landsat images. The results show that the temporal variability of GIMMS and MODIS NDVI allows to delimit similar homogeneous regions in order to mapping the main vegetation cover. MODIS series shows a greater detail in the definition of the regions, but with compatibility with those generated by GIMMS. The temporal dynamics show a typical seasonal pattern, with variations of NDVI amplitude between the groups, that allow to monitor phenological changes. The deviations from calibration between times series are linear, which would facilitate a correction in order to construct a long synthetic time series for studies of land cover change.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652021000501006
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202120201278
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.93 n.3 2021
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
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instname_str Academia Brasileira de Ciências (ABC)
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reponame_str Anais da Academia Brasileira de Ciências (Online)
collection Anais da Academia Brasileira de Ciências (Online)
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