@InProceedings{MascaroFerr:2003:ExÁrIn,
               author = "Mascaro, Sofia de Amorim and Ferreira, Marcos C{\'e}sar",
          affiliation = "{Universidade Estadual Paulista (UNESP). IGCE.} and {Universidade 
                         Estadual Paulista (UNESP). IGE.}",
                title = "An{\'a}lise comparativa entre algor{\'{\i}}tmos de 
                         classifica{\c{c}}{\~a}o digital de imagem com base na 
                         exatid{\~a}o do mapeamento do uso e cobertura do solo: um exemplo 
                         na {\'a}rea de influ{\^e}ncia do reservat{\'o}rio de Jurumirim 
                         - SP",
            booktitle = "Anais...",
                 year = "2003",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria 
                         Garcia",
                pages = "1365 - 1372",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 11. (SBSR).",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "image processing, land-use classification accuracy, error matrix, 
                         Landsat 7, Jurumirim reservoir.",
             abstract = "The most common method employed to accuracy assessment of land-use 
                         and land-cover maps, obtained from remote sensing data and digital 
                         processing, is based in error matrix analysis. In this paper some 
                         of the supervised classification algorithms are tested and 
                         compared to determine the classifications that produces the most 
                         accuracy results. The area used to evaluate the classifiers is 
                         located in southwest of S{\~a}o Paulo State, Brazil, near of 
                         Jurumirim reservoir. The results show that, in relation to global 
                         accuracy, maxlike is the best classifier, and the minimum distance 
                         classifier is the best for Cerrado forest category mapping.",
  conference-location = "Belo Horizonte",
      conference-year = "5-10 abr. 2003",
                 isbn = "85-17-00017-X",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "ltid.inpe.br/sbsr/2002/11.15.13.13",
                  url = "http://urlib.net/ibi/ltid.inpe.br/sbsr/2002/11.15.13.13",
           targetfile = "12_250.pdf",
                 type = "Monitoramento e Modelagem Ambiental / Environmental Monitoring and 
                         Modeling",
        urlaccessdate = "15 jun. 2024"
}