@InProceedings{BastosFonKorDuqSan:2013:CoAn,
               author = "Bastos, Vanessa da Silva Brum and Fonseca, Leila Maria Garcia and 
                         Korting, Thales Sehn and Duque, C. M. and Santos, Rafael Duarte 
                         Coelho dos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and Pinho Centro de Pol{\'{\i}}tica 
                         e Economia Do Setor P{\'u}blico (CEPESP), Funda{\c{c}}{\~a}o 
                         Get{\'u}lio Vargas (FGV-SP), S{\~a}o Paulo, Brazil and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Intraurban land cover classification using IKONOS II images and 
                         data mining techniques: A comparative analysis",
            booktitle = "Proceedings...",
                 year = "2013",
                pages = "214--217",
         organization = "Joint Urban Remote Sensing Event - JURSE 2013.",
              address = "Sao Paulo",
             keywords = "Classification accuracy, Classification algorithm, Classification 
                         process, Comparative analysis, Geographic objects, High spatial 
                         resolution images, Land cover classification, Processing time, 
                         Algorithms, Image analysis, Remote sensing, Data mining.",
             abstract = "High spatial resolution image analysis acquired over urban areas 
                         has been performed with success using Geographic Object Based 
                         Analysis (GEOBIA). However, it was observed that the use of data 
                         mining techniques in the image analysis procedures can speed up 
                         the processing time by selecting the most appropriate parameters 
                         for classification process without decreasing the classification 
                         accuracy. Therefore, this work aims at comparing some algorithms 
                         for classifying intra-urban land cover using IKONOS II images and 
                         data mining techniques. Three classification algorithms, KNN, MLP 
                         and C4.5 were analyzed. © 2013 IEEE.",
                  doi = "10.1109/JURSE.2013.6550703",
                  url = "http://dx.doi.org/10.1109/JURSE.2013.6550703",
                 isbn = "9781479902132",
                label = "scopus 2013-11",
             language = "en",
        urlaccessdate = "13 maio 2024"
}