@InProceedings{ColaresNuneSousFern:2013:MaCoTe,
               author = "Colares, Igor Vieira Vargas and Nunes, Marlon Thiago de Oliveira 
                         and Sousa, Gustavo Mota de and Fernandes, Manoel do Couto",
                title = "Mapeamento da cobertura da terra do Parque Nacional do Itatiaia 
                         com a plataforma cognitiva InterIMAGE",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "2329--2336",
         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 first Conservation Unit (CU) categorized as Park, with full 
                         protection, was Itatiaia National Park (PNI), created in June 
                         1937. This site counts with an area of approximately 30,000 
                         hectares and diverse phenomena to be observed. The remote sensing 
                         and its applications constitute important tools for local 
                         environmental studies. The objective of this study is to build a 
                         land cover map using an open source software that is developed by 
                         InterIMAGE Laboratory of Computer Vision - LVC / PUC-Rio along 
                         with the Division of Image Processing - DPI / INPE and Division 
                         Remote Sensing - DPI / INPE. Through the object-based 
                         classification (OBIA) methodology - which uses as material an 
                         AVNIR-2/ALOS image and digital elevation model -, it was possible 
                         to classify the image in two stages with different classes for 
                         general purpose: vegetation areas extraction, no vegetation and 
                         shade. The vegetation area was identified by NDVI and refined by 
                         altimetric data highlighting areas of montane forest and high 
                         altitude field. For areas with no vegetation, classification 
                         occurred through Analysis Manager module embedded in the software 
                         which has identified, through attributes water classes, urban, 
                         rock, fire and cloud. Shaded areas were identified by arithmetic 
                         means of the bands. The study showed promising results using the 
                         Kappa index of 0.70 and an overall accuracy of 75%.",
  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 = "716",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GFJ4",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GFJ4",
           targetfile = "p0716.pdf",
                 type = "Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o de Dados",
        urlaccessdate = "06 maio 2024"
}