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
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/224780 |
Resumo: | 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 defi ning 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 defi nition 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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Cordeiro, Ana Paula AssumpçãoAlves, Rita de Cássia MarquesSteffler, Ana Paula L. W.Mengue, Vagner PazFontana, Denise CybisRoglio, Vinícius SerafiniGuasselli, Laurindo Antônio2021-07-29T04:31:30Z20210001-3765http://hdl.handle.net/10183/224780001128581This 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 defi ning 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 defi nition 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.application/pdfengAnais da Academia Brasileira de Ciências, Rio de Janeiro, RJ. Vol. 93, No. 3, (2021), e20201278, p. 1-15AgriculturaPastagemCobertura vegetalFlorestasGIMMSMODISRio Grande do SulAgricultureClassificationClusteringForestGrasslandKmeansClassification 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 setsEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001128581.pdf.txt001128581.pdf.txtExtracted Texttext/plain46421http://www.lume.ufrgs.br/bitstream/10183/224780/2/001128581.pdf.txtfca866b38184a74b88749c7a57785f76MD52ORIGINAL001128581.pdfTexto completo (inglês)application/pdf964949http://www.lume.ufrgs.br/bitstream/10183/224780/1/001128581.pdf646b75758921dd8eedd3a04a283f49a2MD5110183/2247802021-08-18 04:48:26.045121oai:www.lume.ufrgs.br:10183/224780Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-08-18T07:48:26Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.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 Assumpção Agricultura Pastagem Cobertura vegetal Florestas GIMMS MODIS Rio Grande do Sul 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 Assumpção |
author_facet |
Cordeiro, Ana Paula Assumpção Alves, Rita de Cássia Marques Steffler, Ana Paula L. W. Mengue, Vagner Paz Fontana, Denise Cybis Roglio, Vinícius Serafini Guasselli, Laurindo Antônio |
author_role |
author |
author2 |
Alves, Rita de Cássia Marques Steffler, Ana Paula L. W. Mengue, Vagner Paz Fontana, Denise Cybis Roglio, Vinícius Serafini Guasselli, Laurindo Antônio |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Cordeiro, Ana Paula Assumpção Alves, Rita de Cássia Marques Steffler, Ana Paula L. W. Mengue, Vagner Paz Fontana, Denise Cybis Roglio, Vinícius Serafini Guasselli, Laurindo Antônio |
dc.subject.por.fl_str_mv |
Agricultura Pastagem Cobertura vegetal Florestas GIMMS MODIS Rio Grande do Sul |
topic |
Agricultura Pastagem Cobertura vegetal Florestas GIMMS MODIS Rio Grande do Sul Agriculture Classification Clustering Forest Grassland Kmeans |
dc.subject.eng.fl_str_mv |
Agriculture Classification Clustering Forest Grassland Kmeans |
description |
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 defi ning 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 defi nition 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.accessioned.fl_str_mv |
2021-07-29T04:31:30Z |
dc.date.issued.fl_str_mv |
2021 |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/224780 |
dc.identifier.issn.pt_BR.fl_str_mv |
0001-3765 |
dc.identifier.nrb.pt_BR.fl_str_mv |
001128581 |
identifier_str_mv |
0001-3765 001128581 |
url |
http://hdl.handle.net/10183/224780 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Anais da Academia Brasileira de Ciências, Rio de Janeiro, RJ. Vol. 93, No. 3, (2021), e20201278, p. 1-15 |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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