@InProceedings{AlcântaraWaBaOgCuSt:2014:EmApHy,
               author = "Alc{\^a}ntara, Enner and Watanabe, Fernanda and Barbosa, 
                         Cl{\'a}udio Clemente Faria and Ogashawara, Igor and Curtarelli, 
                         Marcelo Pedroso and Stech, Jos{\'e} Luiz",
          affiliation = "USP, Department of Cartography, Presidente Prudente, SP, Brazil 
                         and USP, Department of Cartography, Presidente Prudente, SP, 
                         Brazil 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 empirical approach for hyperspectral remote sensing of 
                         chlorophyll-a concentration in Funil hydroelectric reservoir (Rio 
                         de Janeiro State, Brazil)",
            booktitle = "Proceedings...",
                 year = "2014",
                pages = "1--4",
         organization = "International Geoscience and Remote Sensing Symposium, (IGARSS).",
            publisher = "IEEE",
             keywords = "Empirical models, Hyperspectral remote sensing, Chlorophyll-a, 
                         Hydroelectric reservoirs.",
             abstract = "Chlorophyll-a (Chl-a) concentration is adopted as an indicator of 
                         water quality, especially of eutrophic stage. This information is 
                         useful for the management of water quality and the monitoring of 
                         water pollution. Traditional water quality monitoring is expensive 
                         and time consuming. These factors are particularly problematic if 
                         the water bodies to be examined are large. Moreover traditional 
                         techniques also bring about a high probability of undersampling. 
                         Conversely, remote sensing is a powerful tool to assess aquatic 
                         systems and is particularly useful in remote areas [1]. Models to 
                         estimate Chl-a concentrations are commonly empirically or 
                         semi-analytically based. Empirical approaches rely on a specific 
                         spectral feature, such as a spectral ratio modeled to biophysical 
                         measurements using statistical regression [2]. The objective of 
                         this work is to empirically search for best wavelength to develop 
                         statistical models to retrieve the Chl-a concentration in a 
                         tropical hydroelectric reservoir in Brazil.",
  conference-location = "Qu{\'e}bec",
                 isbn = "9781479957750",
                label = "lattes: 7417849872779783 5 Alc{\^a}ntaraWaBaOgCuSt:2014:EmApHy",
             language = "en",
        urlaccessdate = "24 abr. 2024"
}