@InProceedings{BrêdaCorrPaiv:2017:ReNíAg,
               author = "Br{\^e}da, Jo{\~a}o Paulo Lyra Fialho and Correa, Sly Wongchuig 
                         and Paiva, Rodrigo Cauduro Dias",
                title = "Rela{\c{c}}{\~a}o entre n{\'{\i}}veis de agua de Altimetria 
                         Espacial e {\'a}rea inundada a partir de imagens SAR, em 
                         v{\'a}rzeas do rio Purus",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "949--956",
         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 = "In situ data in large basins as the Amazon are usually difficult 
                         to acquire, mainly due to their extension and inaccessibility as 
                         well. To that end, remote sensing technologies that provide 
                         hydrology information have advanced in the last decades. Regarding 
                         altimetry, satellites as the ENVISAT has brought a broad database 
                         in water surface elevation of large surface water bodies. However, 
                         ENVISAT has a 35 day cycle and a relatively sparse ground-track, 
                         which limit the range of observations. In addition, the SAR 
                         technology is pointed as an interesting option for floodplain 
                         detection, which are important not only for the ecosystem but also 
                         for the hydrodynamics process of a large river basin as the 
                         Amazon. Considering that the floodplain area and the river surface 
                         water level are related, it is reasonable to assume that both kind 
                         of information could be combined to enlarge hydrologic database. 
                         Thus this study tested a level series obtained from floodplains 
                         classification of the ALOS PALSAR ScanSAR sensor images at the 
                         Purus Basin. The results indicate that the water level estimated 
                         from an exponential regression of the floodplain area percentage 
                         resulted in a high correlation (0,967) with the in situ level 
                         station. Although the ENVISAT levels absolute mean error is 5,5 
                         times lower than the levels fitted by floodplain area percentage, 
                         this paper has shown that the combination of both series improved 
                         surface water level estimation.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59521",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS4FSB",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS4FSB",
           targetfile = "59521.pdf",
                 type = "Hidrologia",
        urlaccessdate = "27 abr. 2024"
}