@InProceedings{SoaresMelBapBarCru:2017:ClÁgBa,
               author = "Soares, Fernanda Silva and Mello, Gustavo Vaz de and Baptista 
                         Neto, Jos{\'e} Ant{\^o}nio and Barros, Rafael Silva de and Cruz, 
                         Carla Bernadete Madureira",
                title = "Classifica{\c{c}}{\~a}o das {\'A}guas da Ba{\'{\i}}a de 
                         Guanabara utilizando o sensor OLI/Landsat 8",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2091--2098",
         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 = "Monitoring coastal water bodies is a critical to water quality 
                         managing and for the understanding the dynamics of these 
                         environments. In this context, the use of remote sensing allows 
                         the obtaining of synoptic information of water properties helping 
                         in this understanding. The Guanabara Bay is a complex estuarine 
                         environment that has an intense anthropic interference that 
                         contributes to an increase of the contribution of several 
                         optically active components in the water, being a water situation 
                         of Case-2. The aim of this work is to determine different types of 
                         water in Guanabara Bay using the technique of classification and 
                         data mining. The classification technique, performed using the 
                         Ecognition8.9 program, was applied to an image of the OLI/Landsat8 
                         sensor, related to the dry period. Seven types of water were 
                         detected that had a well defined and distinct characteristics of 
                         reflectance. After some tests, combining several descriptors, some 
                         classifications were generated that presented patterns of 
                         distribution of similar types of water, where an east-west lateral 
                         gradient in the central region, different waters in the bottom to 
                         the northeast and northwest, a water class characteristic of the 
                         central channel and another in the contact of the estuary with the 
                         ocean. The use of the classification technique proved to be 
                         effective, even when applied in a coastal water body during a 
                         period of low river flow, allowing the visualization and 
                         identification of the different types of water related to the 
                         hydrodynamic characteristics and the disposal of the various 
                         tributaries in their environment.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59577",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLPUB",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLPUB",
           targetfile = "59577.pdf",
                 type = "Oceanografia e sistemas costeiros",
        urlaccessdate = "27 abr. 2024"
}