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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
01/03/2011 |
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Data da última atualização: |
15/03/2011 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
SANTOS, W. J. R. dos; ALVES, H. M. R.; VIEIRA, T. G. C.; VOLPATO, M. M. L. |
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Afiliação: |
WALBERT JÚNIOR REIS DOS SANTOS, UFLA/EPAMIG; HELENA MARIA RAMOS ALVES, SAPC; TATIANA GROSSI CHQUILOF VIEIRA, EPAMIG; MARGARETE MARIN LORDELO VOLPATO, EPAMIG. |
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Título: |
Influência do declive na exatidão do classificador MAXVER para o mapeamento da cultura do café. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 14., 2009, Natal. |
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Idioma: |
Português |
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Conteúdo: |
This work evaluates the influence of slope in the classification of remotely sensed images used to map coffee lands of the region of Três Pontas in the state of Minas Gerais in Brazil. A Landsat image from 07/16/2008, restaured to 10 m, was used for both, the visual classification, considered as reference map, and the supervised classification using the maximum likelihood algorithm, Maxver, available in the GIS SPRING. Slope information was obtained from SRTM data, which were segmented in classes with intervals of 4% of declivity. To assess the influence of slope in the supervised classification the two maps were overlaid in order to obtain a third map with the confusion areas, i.e. the areas which were classified as coffee plantations by the maxver algorithm but were not coffee in the reference map. This third map, with the confusion areas, was then overlaid onto the slope map. The results showed that most of the areas wrongly classified were at slopes classes of more than 12% of declivity, demonstrating the influence of the relief in the performance of the maxver classifier. |
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Palavras-Chave: |
Classificação de imagem; Image classification; Land use mapping; Mapa do uso da terra; Máxima verossimilhan ça; Maximum likelihood classifier. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/29138/1/Influencia-do-declive.pdf
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Marc: |
LEADER 01834nam a2200217 a 4500
001 1880120
005 2011-03-15
008 2009 bl uuuu u00u1 u #d
100 1 $aSANTOS, W. J. R. dos
245 $aInfluência do declive na exatidão do classificador MAXVER para o mapeamento da cultura do café.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 14., 2009, Natal.$c2009
520 $aThis work evaluates the influence of slope in the classification of remotely sensed images used to map coffee lands of the region of Três Pontas in the state of Minas Gerais in Brazil. A Landsat image from 07/16/2008, restaured to 10 m, was used for both, the visual classification, considered as reference map, and the supervised classification using the maximum likelihood algorithm, Maxver, available in the GIS SPRING. Slope information was obtained from SRTM data, which were segmented in classes with intervals of 4% of declivity. To assess the influence of slope in the supervised classification the two maps were overlaid in order to obtain a third map with the confusion areas, i.e. the areas which were classified as coffee plantations by the maxver algorithm but were not coffee in the reference map. This third map, with the confusion areas, was then overlaid onto the slope map. The results showed that most of the areas wrongly classified were at slopes classes of more than 12% of declivity, demonstrating the influence of the relief in the performance of the maxver classifier.
653 $aClassificação de imagem
653 $aImage classification
653 $aLand use mapping
653 $aMapa do uso da terra
653 $aMáxima verossimilhan ça
653 $aMaximum likelihood classifier
700 1 $aALVES, H. M. R.
700 1 $aVIEIRA, T. G. C.
700 1 $aVOLPATO, M. M. L.
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