@InProceedings{MazzeoDelaMarqRied:2013:EsCaEn,
               author = "Mazzeo, Bruna Christofoletti and Delaneze, Marcelo Elias and 
                         Marques, Mara L{\'u}cia and Riedel, Paulina Setti",
                title = "Avalia{\c{c}}{\~a}o do m{\'e}todo de classifica{\c{c}}{\~a}o 
                         baseada no objeto em imagens de alta resolu{\c{c}}{\~a}o 
                         espacial aplicado para o monitoramento de faixa de dutos: estudo 
                         de caso no entorno da refinaria de Capuava, Mau{\'a}-SP",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "3924--3931",
         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 Metropolitan Region of S{\~a}o Paulo is the most populous of 
                         the country, this happens because of their great economic 
                         importance on the national scene. This fact results in intense 
                         population growth and urban expansion, reaching some non-habitable 
                         places of the metropolis, as areas of pipelines, which are very 
                         important for the transportation of natural gas, oil and its 
                         derivatives. With the disorderly occupation is generated great 
                         anthropogenic pressure on the ducts, causing risks to people who 
                         are close to them. Therefore, this study aims to monitor a stretch 
                         of pipeline GASPAL / OSVAT and Capuava Refinery (RECAP), located 
                         on the outskirts of the metropolitan area of S{\~a}o Paulo in the 
                         city of Mau{\'a}, using remote sensing and GIS. The monitoring 
                         was performed by the object classification based on satellite 
                         images Ikonos and RapidEye, and image processing, detection of 
                         objects, segmentation, classification and editing were developed 
                         through the eCognition and ArcGIS. To determine the statistical 
                         accuracy of the mapping of land cover the stretch of pipeline in 
                         Maua, the results were analyzed by matrix errors and the Kappa 
                         coefficient. The results presented in the paper show that the 
                         methodological procedure of classification based on the object 
                         presents itself as a good alternative for monitoring pipeline 
                         ranges, as well as the use of high resolution image sensors.",
  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 = "1506",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GLP8",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GLP8",
           targetfile = "p1506.pdf",
                 type = "Geoprocessamento e Aplica{\c{c}}{\~o}es",
        urlaccessdate = "15 jun. 2024"
}