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@InProceedings{AlcantaraCuOgRoKaSt:2015:DeQARe,
               author = "Alcantara, Enner and Curtarelli, Marcelo Pedroso and Ogashawara, 
                         Igor and Rosan, Thais and Kampel, Milton and Stech, Jos{\'e} 
                         Luiz",
          affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Purdue University Indianopolis} 
                         and {Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Developing QAA-based retrieval model of total suspended matter 
                         concentration in Itumbiara reservoir, Brazil",
                 year = "2015",
         organization = "IEEE International Geoscience and Remote Sensing Symposium 
                         (IGARSS)",
             abstract = "High concentrations of total suspended matter (TSM) reduce water 
                         clarity which can affect photosynthesis of submerged aquatic 
                         vegetation, thereby affecting oxygen production which is essential 
                         to aquatic organisms at upper levels in the food chain. The aim of 
                         this work was to evaluate the use of Landsat-8 Operational Land 
                         Imager (OLI) sensor to estimate total suspended matter (TSM) 
                         concentrations in the Itumbiara hydroelectric reservoir (IHR), 
                         Midwest Brazil. A TSM model was obtained based on the particle 
                         backscattering at 561 nm. The calibrated model, based on the 
                         particle backscattering derived from the QuaseAnalytical Algorithm 
                         (QAA), TSM = (1.2265e-7.197xb bp561 )+\ξ , shown an R 2 = 
                         0.69. The validation shown an R2 = 0.63, %RMSE = 2.90 and a mean 
                         bias of -0.37 mg L-1 .",
  conference-location = "Milan, Italy",
      conference-year = "23-31 July",
        urlaccessdate = "27 nov. 2020"
}


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