@InProceedings{PedreiraFidaPradAraú:2011:ClDiIm,
               author = "Pedreira, Bernadete da Concei{\c{c}}{\~a}o Carvalho Gomes and 
                         Fidalgo, Elaine Cristina Cardoso and Prado, Rachel Bardy and 
                         Ara{\'u}jo, Rodrigo de S{\'a}",
          affiliation = "{Empresa Brasileira de Pesquisa Agropecu{\'a}ria – EMBRAPA SOLOS} 
                         and {Empresa Brasileira de Pesquisa Agropecu{\'a}ria – EMBRAPA 
                         SOLOS} and {Empresa Brasileira de Pesquisa Agropecu{\'a}ria – 
                         EMBRAPA SOLOS} and {Universidade Federal do Rio de Janeiro – IG 
                         /UFRJ}",
                title = "Classifica{\c{c}}{\~a}o digital de imagens de sat{\'e}lite de 
                         alta resolu{\c{c}}{\~a}o espacial para o mapeamento de uso e 
                         cobertura da terra na {\'a}rea do complexo petroqu{\'{\i}}mico 
                         do Rio de Janeiro",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7340--7347",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "imagem Quickbird, classificador pixel a pixel, ENVI, Quickbird 
                         image, pixel by pixel classificator, ENVI.",
             abstract = "The mapping of the land use and cover in the area of the 
                         Petrochemical Complex of Rio de Janeiro (COMPERJ) is needed for 
                         identification and monitoring of environmental changes that are 
                         expected with its implementation. Then, this work aimed to select 
                         the best options of automatic classification to perform this 
                         mapping. The methodology involved the following steps: 
                         organization of the digital cartographic database, selection of 
                         better Quickbird satellite image to cover study area, digital 
                         image processing in software ENVI 4.5 and ArcGIS 9.3.1 from ESRI, 
                         verification of spectral patterns of mapped classes in field and 
                         preparation of the final map in scale 1: 15,000. Nine land use and 
                         cover classes were obtained and the results showed that the 
                         methodology adopted, supervised classification image using 
                         automatic classifiers pixel by pixel, was efficient for the 
                         separation of the main targets of interest, avoiding large scan 
                         job. However, it was found that the classification pixel by pixel, 
                         applied in high-resolution images, creates many isolated pixels 
                         and jagged edges due to the level of detail of these images. One 
                         solution to this problem would be to use programs that make image 
                         classification by regions and object-oriented. However, the cost 
                         of these programs is high. The verification work was essential to 
                         terrestrial confirmation of the mapped classes, which are often 
                         confused in the visual image as well as by the classifier used.",
  conference-location = "Curitiba",
      conference-year = "30 abr. - 5 maio 2011",
                 isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW/3A68E85",
                  url = "http://urlib.net/ibi/3ERPFQRTRW/3A68E85",
           targetfile = "p0336.pdf",
                 type = "Processamento de Imagens",
        urlaccessdate = "15 jun. 2024"
}