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| SANTOS, W. J. R. dos; ALVES, H. M. R.; VIEIRA, T. G. C.; VOLPATO, M. M. L.. |
| 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... |
| Tipo: Artigo em anais de congresso (ALICE) |
Palavras-chave: Mapa do uso da terra; Classificação de imagem; Máxima verossimilhan ça; Land use mapping; Image classification; Maximum likelihood classifier. |
| Ano: 2009 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/880120 |
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