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@Article{CairoBLNCMFSC:2020:HyChAl,
               author = "Cairo, Carolline Tressmann and Barbosa, Cl{\'a}udio Clemente 
                         Faria and Lobo, Felipe de Lucia and Novo, Evlyn M{\'a}rcia 
                         Le{\~a}o de Moraes and Carlos, Felipe Menino and Maciel, Daniel 
                         Andrade and Flores Junior, Rog{\'e}rio and Silva, Edson Filisbino 
                         Freire da and Curtarelli, Victor Pedroso",
          affiliation = "{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)} 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)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Hybrid chlorophyll-a algorithm for assessing trophic states of a 
                         tropical brazilian reservoir based on MSI/Sentinel-2 data",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "1",
                pages = "e12010040",
             keywords = "Hybrid Chlorophyll-a Algorithm, monitoramento da qualidade da 
                         {\'a}gua, clorofila-a.",
             abstract = "Using remote sensing for monitoring trophic states of inland 
                         waters relies on the calibration of chlorophyll-a (chl-a) 
                         bio-optical algorithms. One of the main limiting factors of 
                         calibrating those algorithms is that they cannot accurately cope 
                         with the wide chl-a concentration ranges in optically complex 
                         waters subject to different trophic states. Thus, this study 
                         proposes an optical hybrid chl-a algorithm (OHA), which is a 
                         combined framework of algorithms for specific chl-a concentration 
                         ranges. The study area is Ibitinga Reservoir characterized by high 
                         spatiotemporal variability of chl-a concentrations (31000 mg/m3 ). 
                         We took the following steps to address this issue: (1) we defined 
                         optical classes of specific chl-a concentration ranges using 
                         Spectral Angle Mapper (SAM); (2) we calibrated/validated chl-a 
                         bio-optical algorithms for each trophic class using simulated 
                         Sentinel-2 MSI (Multispectral Instrument) bands; (3) and we 
                         applied a decision tree classifier in MSI/Sentinel-2 image to 
                         detect the optical classes and to switch to the suitable algorithm 
                         for the given class. The results showed that three optical classes 
                         represent different ranges of chl-a concentration: class 1 varies 
                         2.8922.83 mg/m3 , class 2 varies 19.5187.63 mg/m3 , and class 3 
                         varies 75.89938.97 mg/m3 . The best algorithms for trophic classes 
                         1, 2, and 3 are the 3-band (R2 = 0.78; MAPE - Mean Absolute 
                         Percentage Error = 34.36%), slope (R2 = 0.93; MAPE = 23.35%), and 
                         2-band (R2 = 0.98; MAPE = 20.12%), respectively. The decision tree 
                         classifier showed an accuracy of 95% for detecting SAMs optical 
                         trophic classes. The overall performance of OHA was satisfactory 
                         (R2 = 0.98; MAPE = 26.33%) using in situ data but reduced in the 
                         Sentinel-2 image (R2 = 0.42; MAPE = 28.32%) due to the temporal 
                         gap between matchups and the variability in reservoir 
                         hydrodynamics. In summary, OHA proved to be a viable method for 
                         estimating chl-a concentration in Ibitinga Reservoir and the 
                         extension of this framework allowed a more precise chl-a estimate 
                         in eutrophic inland waters.",
                  doi = "10.3390/rs12010040",
                  url = "http://dx.doi.org/10.3390/rs12010040",
                 issn = "2072-4292",
                label = "lattes: 1596449770636962 2 CairoBLNCMFSC:2020:HyChAl",
             language = "en",
           targetfile = "cairo_remote.pdf",
        urlaccessdate = "19 abr. 2021"
}


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