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@InProceedings{GlerianiFerrSoar:2013:CoMoLi,
               author = "Gleriani, Jos{\'e} Marinaldo and Ferreira, Pedro Henrique Silva 
                         and Soares, Vicente Paulo",
                title = "Compara{\c{c}}{\~a}o de Modelo Linear de Mistura Espectral 
                         (MLME) e Modelo N{\~a}o Linear de Mistura Espectral (MNLME) 
                         aplicados {\`a} dados TM/Landsat-5 com dados subpixel do sensor 
                         RapidEye",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "1298--1305",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Linear Spectral Mixture Models (MLME) have been widely used for 
                         equating the proportion of components within a mixed pixel. 
                         However, some authors have investigated using nonlinear Spectral 
                         Mixture (MNLME) in modeling these components. In this study, the 
                         MLME was compared with MNLME which run through a supervised MLP 
                         (Multilayer Perceptrons) network where TM / Landsat (30m) data 
                         were used as input layer. Data used as output layer included the 
                         proportion of the components obtained from a Rapideye scene (5m) 
                         considering two situations: the proportion of components (shade, 
                         vegetation and sand) after MaxVer classification and the 
                         proportion of components after application of the MLME in the 
                         Rapideye image. The choice of the best model was based on the 
                         total mean absolute error, with the MLME having provided a better 
                         fit of the proportions of mixed pixel.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "369",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GCSM",
                  url = "http://urlib.net/rep/3ERPFQRTRW34M/3E7GCSM",
           targetfile = "p0369.pdf",
                 type = "An{\'a}lise e Aplica{\c{c}}{\~a}o de Dados de Alta e Baixa 
                         Resolu{\c{c}}{\~a}o Espacial",
        urlaccessdate = "22 jan. 2021"
}


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