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@InProceedings{SaitoArguMore:2013:MiDaAn,
               author = "Saito, Nath{\'a}lia Suemi and Arguello, Fernanda Viana Paiva and 
                         Moreira, Maur{\'{\i}}cio Alves",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Minera{\c{c}}{\~a}o de dados para an{\'a}lise da cobertura 
                         florestal",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "2400--2407",
         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 landscape ecology metrics associated with spectral and space 
                         data mining can be used to increase the potential of the analysis 
                         and applications of remote sensing data becoming an important tool 
                         for decision making. The present study sought to use data mining 
                         techniques and metrics of landscape ecology to classify and 
                         quantify the different types of vegetation present in S{\~a}o 
                         Luis do Paraitinga city, Sao Paulo, Brazil. The images went 
                         through object-oriented analysis through the plugin GeoDMA to 
                         obtain spectral and spatial data. This information was used to 
                         classify classes by decision trees. Eucalyptus and Forest fragment 
                         areas represented 8.6% and 36,1% of the total area, respectively. 
                         The decision tree generated by the classification algorithm was 
                         used to obtain the map of forest cover. The classification by 
                         decision tree showed kappa of 0.80, indicating little confusion. 
                         The results indicate the importance of the forest sector and 
                         contribute in studies to contain the impacts and problems caused 
                         by the expansion of eucalyptus plantations in the municipality. 
                         The generation of classifications by the method of data mining 
                         metrics associated with landscape ecology proved to be an 
                         affordable and reliable tool to extract the spatial and spectral 
                         data with remote sensing techniques. The method was efficient for 
                         the separation of forest classes and the metrics used were 
                         important to better understand the objects inserted in the 
                         landscape and the pressures they suffer.",
  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 = "1444",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GLCP",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GLCP",
           targetfile = "p1444.pdf",
                 type = "Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o de Dados",
        urlaccessdate = "2022, Jan. 22"
}


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