@InProceedings{AlfayaReisFlorBarb:2013:ClĮrAl,
               author = "Alfaya, Felipe Augusto Ventura da Silva and Reis, Mariane Souza 
                         and Florenzano, Teresa Gallotti and Barbosa, Cl{\'a}udio Clemente 
                         Faria",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Classifica{\c{c}}{\~a}o de {\'a}reas alag{\'a}veis da 
                         plan{\'{\i}}cie do rio Amazonas utilizando minera{\c{c}}{\~a}o 
                         de dados e GEOBIA",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "2306--2313",
         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 = "The study of the Amazon River floodplain is of great importance 
                         for many subjects. The accurate definition of its area is the 
                         first challenge for this study. An important source of data for 
                         this is the SRTM Digital Elevation Model. The objective of this 
                         work is to evaluate the use of data mining procedures to map 
                         wetlands in the Amazon River floodplain, using SRTM data and HAND. 
                         The results obtained from data mining were compared with 
                         classifications created using manual selection of attributes. To 
                         apply the method two reaches of this floodplain were selected: 
                         Codaj{\'a}s, localized in Amazonas State, and {\'O}bidos, 
                         localized in Par{\'a} State. The classifications were carried out 
                         using two segmentation levels and decision trees built using the 
                         J48 algorithm implemented in WEKA. The layers of SRTM-DEM, 
                         HAND-DEM and HAND-DEM derived slope and curvature images were used 
                         in the classification. A Monte Carlo method based analysis was 
                         used to evaluate the level of agreement between the 
                         classifications and a reference map. Those results were compared 
                         to maps created with manual selection of attributes. For the 
                         {\'O}bidos reach, both manual selection and data mining yielded 
                         similar results but for the Codaj{\'a}s reach the data mining 
                         method performed noticeably better as indicated by the Monte Carlo 
                         analisys.",
  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 = "313",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GCGU",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GCGU",
           targetfile = "p0313.pdf",
                 type = "Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o de Dados",
        urlaccessdate = "06 maio 2024"
}