@InProceedings{OliveiraContSantArag:2017:PrDiIm,
               author = "Oliveira, Alarcon Matos and Conti, Jos{\'e} Bueno and Santos, 
                         Rosangela Leal and Arag{\~a}o, Lusanira Nogueira",
                title = "Processamento digital de imagens para determina{\c{c}}{\~a}o do 
                         coeficiente de Manning na regi{\~a}o da Barragem de S{\~a}o 
                         Jos{\'e} do Jacu{\'{\i}}pe - BA",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3902--3909",
         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 = "Simulations of hydrological models constitute a powerful ferment 
                         for evaluation and environmental management, aiding in decision 
                         making. The scale of complexity of these models requires special 
                         attention, especially when working with surface runoff of open 
                         channels, since in this context a variable appears, which is not 
                         well worked will imply in incoherent results, this is the 
                         coefficient of Manning. The Manning coefficient corresponds to the 
                         opposite force to the flow, the determination of this coefficient 
                         is preponderant to indicate the resistance of the flow in the 
                         channel, so it is not a simplistic task since there are no exact 
                         methods for its determination. The present paper had the objective 
                         of applying digital image processing PDI - color composition and 
                         supervised classification, using the Maximum Likelihood algorithm 
                         - Maxvers Landsat Image 08, TM + sensor of February of 2015 with 
                         spatial resolution of 30 meters 16bits spectral resolution, 
                         cartographic projection WGS84, 24Sul spindle with the intention of 
                         mapping the Manning classes to the municipality of S{\~a}o 
                         Jos{\'e} do Jacu{\'{\i}}pe, especially in the area between the 
                         S{\~a}o Jos{\'e} do Jacu{\'{\i}}pe Dam and the Urban area of 
                         this city. The choices of the classes were according to (DE JONG 
                         et al., 2003; CAMPOS, 2011). Based on the evaluation of the 
                         accuracy of the results, field work and visual identification, 
                         this technique proved adequate for this mapping, and it is 
                         advisable to use it in future work.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60067",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM27B",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM27B",
           targetfile = "60067.pdf",
                 type = "Hidrologia",
        urlaccessdate = "27 abr. 2024"
}