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@Article{OliveiraFKCBVGPFP:2016:AsReSe,
               author = "Oliveira, Eduardo N. and Fernandes, Alexandre M. and Kampel, 
                         Milton and Cordeiro, Renato C. and Brandini, Nilva and Vinzon, 
                         Susana B. and Grassi, Renata M. and Pinto, Fernando N. and 
                         Fillipo, Alessandro M. and Paranhos, Rodolfo",
          affiliation = "{Universidade Federal do Rio de Janeiro (UFRJ)} and {Universidade 
                         Federal do Rio de Janeiro (UFRJ)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Universidade Federal Fluminense 
                         (UFF)} and {Universidade Federal Fluminense (UFF)} and {} and 
                         {Universidade Federal do Rio de Janeiro (UFRJ)} and {Universidade 
                         Federal do Rio de Janeiro (UFRJ)} and {Universidade Federal do Rio 
                         de Janeiro (UFRJ)} and {Universidade Federal do Rio de Janeiro 
                         (UFRJ)}",
                title = "Assessment of remotely sensed chlorophyll-a concentration in 
                         Guanabara Bay, Brazil",
              journal = "Journal of Applied Remote Sensing",
                 year = "2016",
               volume = "10",
               number = "2",
                pages = "026003",
                month = "Apr.",
             keywords = "chlorophyll-a concentration, Guanabara Bay, Medium Resolution 
                         Imaging Spectrometer, Ocean color empirical algorithm, Optical 
                         properties.",
             abstract = "The Guanabara Bay (GB) is an estuarine system in the metropolitan 
                         region of Rio de Janeiro (Brazil), with a surface area of 
                         \∼346 km2 threatened by anthropogenic pressure. Remote 
                         sensing can provide frequent data for studies and monitoring of 
                         water quality parameters, such as chlorophyll-a concentration 
                         (Chl-a). Different combination of Medium Resolution Imaging 
                         Spectrometer (MERIS) remote sensing reflectance band ratios were 
                         used to estimate Chl-a. Standard algorithms such as Ocean Color 
                         3-band, Ocean Color-4 band, fluorescence line height, and maximum 
                         chlorophyll index were also tested. The MERIS Chl-a estimates were 
                         statistically compared with a dataset of in situ Chl-a (2002 to 
                         2012). Good correlations were obtained with the use of green, red, 
                         and near-infrared bands. The best performing algorithm was based 
                         on the red (665 nm) and green (560 nm) band ratio, named {"}RG3{"} 
                         algorithm (r2 = 0.71, chl-a = 62,565\∗x1.6118). The RG3 was 
                         applied to a time series of MERIS images (2003- to 2012). The GB 
                         has a high temporal and spatial variability of Chl-a, with highest 
                         values found in the wet season (October to March) and in some of 
                         the most internal regions of the estuary. Lowest concentrations 
                         are found in the central circulation channel due to the flushing 
                         of ocean water masses promoted by pumping tide.",
                  doi = "10.1117/1.JRS.10.026003",
                  url = "http://dx.doi.org/10.1117/1.JRS.10.026003",
                 issn = "1931-3195",
             language = "en",
           targetfile = "oliveira_assessment.pdf",
        urlaccessdate = "01 dez. 2020"
}


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