@InProceedings{ManabeRochLamp:2015:DiÁrCa,
               author = "Manabe, Victor Danilo and Rocha, Jansle Vieira and Lamparelli, 
                         Rubens Augusto Camargo",
                title = "Diferencia{\c{c}}{\~a}o de {\'a}reas cana de a{\c{c}}{\'u}car 
                         e pastagem atrav{\'e}s de t{\'e}cnicas de minera{\c{c}}{\~a}o 
                         de dados",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2960--2967",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The study of the sugarcane dynamics has a direct influence on the 
                         composition of agricultural production, the direct and indirect 
                         impacts on biodiversity, social and human development and the 
                         definition of public policies, among others. Therefore it becomes 
                         important to map areas of cultivation of sugarcane on a regional 
                         scale using remote sensing. This study aimed to evaluate data 
                         mining techniques to differentiate areas of sugarcane and pasture 
                         using NDVI data from Terra/MODIS sensor. Attribute selection and 
                         balancing classes contributed to the improved performance of 
                         classification models. The best result was using the neural 
                         network classifier (Multilayer Perceptron) with a 72.49% of 
                         accuracy and 0.45 Kappa index. Thus, it was noticed the potential 
                         in the application of data mining techniques for classification of 
                         crops, using time series of vegetation index.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "591",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4AHS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4AHS",
           targetfile = "p0591.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "06 maio 2024"
}