@InProceedings{EndoSiOlKoGhPe:2017:AuMeOp,
               author = "Endo, Clarissa Akemi Kajiya and Silva, Maria Paula and Oliveira, 
                         Raquel Ren{\'o} de and Korting, Thales Sehn and Gherardi, Douglas 
                         Francisco Marcolino and Pezzi, Luciano Ponzi",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "An automatic method for open water detection using MUX/CBERS-4 
                         images",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "4087--4094",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Most of the rivers in the planet have been dammed for providing 
                         water storage for human needs such as energy production, 
                         irrigation and for domestic and industrial use. At present, there 
                         are thousands of reservoirs in the world in need of frequent 
                         monitoring to support proper water resources management. Remote 
                         sensing provides a large amount of data for monitoring the Earth 
                         surface but faces time consuming processes for extracting the 
                         information needed hampers its use for real time management. This 
                         paper describes an automatized method for mapping open water 
                         bodies using MUX/CBERS-4 images in order to speed the process. The 
                         method consists in applying colour transformation in all RGB 
                         combinations of MUX bands transformed to HSV (Hue Saturation 
                         Value) images and empirically defining the optimum Hue interval 
                         for splitting image pixels between two classes: water and 
                         non-water. In order to do that, all RGB compositions of MUX bands 
                         were transformed to HSV images and tested to select the set 
                         providing the best separation between water and non-water. The Hue 
                         interval was used as input for the LEGAL (Linguagem Espacial para 
                         Geoprocessamento Alg{\'e}brico) available at Spring 5.2.7 to 
                         split the Hue image into water and non-water pixels. A statistical 
                         analysis was applied to aid the choice of the best composition. 
                         The RGB 587 was chosen as the best composition to identify water 
                         bodies in MUX images. Future work recommendations include applying 
                         distinct confidence intervals and performing a pre-processing of 
                         the images, including image calibration and atmospheric 
                         correction.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59453",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM2FS",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM2FS",
           targetfile = "59453.pdf",
                 type = "CBERS",
        urlaccessdate = "27 abr. 2024"
}