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@InCollection{OgashawaraCurtAraúStec:2016:BiMoTr,
               author = "Ogashawara, Igor and Curtarelli, Marcelo Pedroso and Ara{\'u}jo, 
                         Carlos Alberto Sampaio de and Stech, Jos{\'e} Luiz",
                title = "Bio-optical modeling in a tropical hypersaline lagoon 
                         environment",
            booktitle = "Environmental applications of remote sensing",
            publisher = "InTech",
                 year = "2016",
               editor = "Marghany, Maged",
                pages = "235--258",
             keywords = "Water quality, chlorophyll-a, turbidity, bio-optical modeling.",
             abstract = "In this chapter, we attempted to present an overview of the use of 
                         remote sensing to mon\‐ itor water quality parameters, 
                         mainly chlorophyll-a (chl-a) and turbidity. We summarized the main 
                         concepts of bio-optical modeling and presented a case study of the 
                         application of the Hyperspectral Imager for the Coastal Ocean 
                         (HICO) for the monitoring of water quality in a tropical 
                         hypersaline aquatic environment. Using HICO, we evaluated a set of 
                         different semi-empirical bio-optical algorithms for chl-a and 
                         turbidity estimation devel\‐ oped for inland and oceanic 
                         waters in the Araruama Lagoon, RJ, Brazil, which is an ex\‐ 
                         treme environment due to its high salinity values. We also 
                         developed an empirical algorithm for both water quality parameters 
                         and compared the performances. Results showed that for chl-a 
                         estimation all models have a low performance with a normalized 
                         root mean square error (NRMSE) varying from 24.13 to 30.46. For 
                         turbidity, the bio-opti\‐ cal algorithms showed a better 
                         performance with the NRMSE between 15.49 and 28.04. Overall, these 
                         results highlight the importance of including extreme 
                         environments, such as the Araruama Lagoon, on the validation of 
                         bio-optical algorithms as well as the need for new orbital 
                         hyperspectral sensors which will improve the development of the 
                         field.",
          affiliation = "{Indiana University} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                  doi = "10.5772/61869",
                  url = "http://dx.doi.org/10.5772/61869",
                 isbn = "978-953-51-2444-3 and 978-953-51-2443-6",
             language = "en",
           targetfile = "ogashawara_bio.pdf",
        urlaccessdate = "25 nov. 2020"
}


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