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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
04/12/2014 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
GONÇALVES, R. R. V.; ZULLO JÚNIOR, J.; AMARAL, B. F.; COLTRI, P. P.; SOUSA, E. P. M.; ROMANI, L. A. S. |
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Afiliação: |
RENATA RIBEIRO DO VALLE GONÇALVES, Cepagri/Unicamp; JURANDIR ZULLO JÚNIOR, Cepagri/Unicamp; BRUNO FERRAZ DO AMARAL, ICMC/USP; PRISCILA PEREIRA COLTRI, Cepagri/Unicamp; ELAINE PARROS MACHADO DE SOUSA, ICMC/USP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA. |
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Título: |
Land use temporal analysis through clustering techniques on satellite image time series. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
In: INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; CANADIAN SYMPOSIUM ON REMOTE SENSING, 35., 2014, Québec. Energy and our changing planet: proceedings. [S.l.]: IEEE, 2014. |
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Páginas: |
p. 2173-2176. |
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Idioma: |
Inglês |
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Notas: |
IGARSS 2014. |
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Conteúdo: |
Satellite images time series have been used to study land surface, such as identification of forest, water, urban areas, as well as for meteorological applications. However, for knowledge discovery in large remote sensing databases can be use clustering techniques in multivariate time series. The clustering technique on three-dimensional time series of NDVI, albedo and surface temperature from AVHRR/NOAA satellite images was used, in this study, to map the variability of land use. This approach was suitable to accomplish the temporal analysis of land use. Additionally, this technique can be used to identify and analyze dynamics of land use and cover being useful to support researches in agriculture, even considering low spatial resolution satellite images. The possibility of extracting time series from satellite images, analyzing them through data mining techniques, such as clustering, and visualizing results in geospatial way is an important advance and support to agricultural monitoring tasks. |
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Palavras-Chave: |
Albedo; Índice de vegetação; K-means; Séries temporais; Temperatura da superfície. |
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Thesaurus Nal: |
surface temperature; Time series analysis; Vegetation index. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01998nam a2200289 a 4500
001 2001636
005 2020-01-08
008 2014 bl uuuu u00u1 u #d
100 1 $aGONÇALVES, R. R. V.
245 $aLand use temporal analysis through clustering techniques on satellite image time series.$h[electronic resource]
260 $aIn: INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; CANADIAN SYMPOSIUM ON REMOTE SENSING, 35., 2014, Québec. Energy and our changing planet: proceedings. [S.l.]: IEEE$c2014
300 $ap. 2173-2176.
500 $aIGARSS 2014.
520 $aSatellite images time series have been used to study land surface, such as identification of forest, water, urban areas, as well as for meteorological applications. However, for knowledge discovery in large remote sensing databases can be use clustering techniques in multivariate time series. The clustering technique on three-dimensional time series of NDVI, albedo and surface temperature from AVHRR/NOAA satellite images was used, in this study, to map the variability of land use. This approach was suitable to accomplish the temporal analysis of land use. Additionally, this technique can be used to identify and analyze dynamics of land use and cover being useful to support researches in agriculture, even considering low spatial resolution satellite images. The possibility of extracting time series from satellite images, analyzing them through data mining techniques, such as clustering, and visualizing results in geospatial way is an important advance and support to agricultural monitoring tasks.
650 $asurface temperature
650 $aTime series analysis
650 $aVegetation index
653 $aAlbedo
653 $aÍndice de vegetação
653 $aK-means
653 $aSéries temporais
653 $aTemperatura da superfície
700 1 $aZULLO JÚNIOR, J.
700 1 $aAMARAL, B. F.
700 1 $aCOLTRI, P. P.
700 1 $aSOUSA, E. P. M.
700 1 $aROMANI, L. A. S.
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