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@InProceedings{CarvalhoKuxFlorSilv:2015:GeObIm,
               author = "Carvalho, Marcus and Kux, Hermann Johann Heinrich and Florenzano, 
                         Teresa Galotti and Silva, Gabriella",
          affiliation = "{Universidade Federal Fluminense (UFF)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Federal do Rio de Janeiro 
                         (UFRJ)}",
                title = "Geographic object-based image analysis (GEOBIA) and data mining 
                         for urban land use classification by blocks using WorldView-2 
                         images",
                 year = "2015",
         organization = "International Cartographic Conference, 27.",
             keywords = "Geographic object-based image analysis, Data mining, Urban land 
                         use by blocks.",
             abstract = "The objective of this study is to develop and evaluate a 
                         methodology for the analysis of WorldView-2 images based on 
                         Geographic Object-Based Image Analysis (GEOBIA) and Data Mining, 
                         to classify urban land use per block. The area under study is a 
                         section at the western part of S{\~a}o Paulo Metropolitan Region. 
                         Mapping land use per urban block is an important information 
                         source for managers and decision makers in urban areas. Among the 
                         land cover classes considered in this work, seven were used by the 
                         S{\~a}o Paulo Municipality in the official maps. Objects located 
                         within the blocks are helpful to characterize these areas. So, in 
                         order to analyze the context and the relationship among classes 
                         for the elaboration of land use mapping per block, a 
                         classification procedure was adopted previously done with good 
                         accuracy considering a lower hierarchical level (sub-objects) at 
                         the level of blocks (super-objects). The steps followed were: 
                         selection and sample collection at the blocks to train the 
                         classifier, choice of attributes to be analyzed by the data mining 
                         algorithm, generation and implementation of a decision tree using 
                         the DEFINIENS Developer software, for the classification of the 
                         WorldView-2 image. It is concluded that the use of the OBIA 
                         paradigm and Data Mining techniques were helpful for mapping urban 
                         land use. The Kappa index was 0.7050 and the global precision 
                         0.7556.",
  conference-location = "Rio de Janeiro, RJ",
      conference-year = "23-28 Aug.",
        urlaccessdate = "29 nov. 2020"
}


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