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 | Acesso ao texto completo restrito à biblioteca da Embrapa Territorial. Para informações adicionais entre em contato com cnpm.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
30/09/2011 |
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Data da última atualização: |
03/05/2019 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
SILVA, G. B. S. da; MELLO, M. P.; SHIMABUKURO, Y. E.; RUDORFF, B. F. T.; VICTORIA, D. de C. |
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Afiliação: |
GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPM; MARCIO PUPIN MELLO, INPE; YOSIO EDEMIR SHIMABUKURO, INPE; BERNARDO FRIEDRICH THEODOR RUDORFF, INPE; DANIEL DE CASTRO VICTORIA, CNPM. |
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Título: |
Multitemporal classification of natural vegetation cover in Brazilian Cerrado. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 6., 2011, Trento, IT. Anais... Trento: IEEE, 2011. |
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Páginas: |
p. 117-120. |
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Idioma: |
Português |
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Conteúdo: |
Spectral-Temporal Analysis by Response Surface (STARS), which utilizes surface response to represent time series spectral-temporal behavior of pixels in satellite images, was used to map and discriminate savanna vegetation classes in portion of Cerrado biome of Mato Grosso State, Brazil, using MODIS data. STARS utilized 16 daily MODIS, cloud-free, images that were collected from September 1st 2008 to August 31st 2009. The Multi-Coefficient Image (MCI) resulted from the STARS was used as input attributes for the three tested classifiers: (i) ML - maximum likelihood; (ii) SVM - support vector machine; and (iii) NN - neural network. The results showed that the NN classifier presented higher kappa coefficient (0.58) and overall accuracy of 68.6%. |
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Palavras-Chave: |
Linear spectral mixture model; Savanna; STARS. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01424nam a2200205 a 4500
001 1901884
005 2019-05-03
008 2011 bl uuuu u00u1 u #d
100 1 $aSILVA, G. B. S. da
245 $aMultitemporal classification of natural vegetation cover in Brazilian Cerrado.
260 $aIn: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 6., 2011, Trento, IT. Anais... Trento: IEEE$c2011
300 $ap. 117-120.
520 $aSpectral-Temporal Analysis by Response Surface (STARS), which utilizes surface response to represent time series spectral-temporal behavior of pixels in satellite images, was used to map and discriminate savanna vegetation classes in portion of Cerrado biome of Mato Grosso State, Brazil, using MODIS data. STARS utilized 16 daily MODIS, cloud-free, images that were collected from September 1st 2008 to August 31st 2009. The Multi-Coefficient Image (MCI) resulted from the STARS was used as input attributes for the three tested classifiers: (i) ML - maximum likelihood; (ii) SVM - support vector machine; and (iii) NN - neural network. The results showed that the NN classifier presented higher kappa coefficient (0.58) and overall accuracy of 68.6%.
653 $aLinear spectral mixture model
653 $aSavanna
653 $aSTARS
700 1 $aMELLO, M. P.
700 1 $aSHIMABUKURO, Y. E.
700 1 $aRUDORFF, B. F. T.
700 1 $aVICTORIA, D. de C.
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Embrapa Territorial (CNPM) |
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