author = "Watanabe, Fernanda and Mishra, Deepak R. and Astuti, Ike and 
                         Rodrigues, Thanan and Alc{\^a}ntara, Enner and Imai, Nilton N. 
                         and Barbosa, Cl{\'a}udio Clemente Faria",
          affiliation = "{Universidade Estadual Paulista (UNESP)} and {University of 
                         Georgia} and {University of Georgia} and {Universidade Estadual 
                         Paulista (UNESP)} and {Universidade Estadual Paulista (UNESP)} and 
                         {Universidade Estadual Paulista (UNESP)} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)}",
                title = "Parametrization and calibration of a quasi-analytical algorithm 
                         for tropical eutrophic waters",
              journal = "ISPRS Journal of Photogrammetry and Remote Sensing",
                 year = "2016",
               volume = "121",
                pages = "28--47",
                month = "Nov.",
             keywords = "Algal bloom, Bio-optical model, Inherent optical properties, 
                         Inland waters, Quasi-analytical algorithm, Remote sensing 
             abstract = "Quasi-analytical algorithm (QAA) was designed to derive the 
                         inherent optical properties (IOPs) of water bodies from 
                         above-surface remote sensing reflectance (Rrs). Several variants 
                         of QAA have been developed for environments with different 
                         bio-optical characteristics. However, most variants of QAA suffer 
                         from moderate to high negative IOP prediction when applied to 
                         tropical eutrophic waters. This research is aimed at parametrizing 
                         a QAA for tropical eutrophic water dominated by cyanobacteria. The 
                         alterations proposed in the algorithm yielded accurate absorption 
                         coefficients and chlorophyll-a (Chl-a) concentration. The main 
                         changes accomplished were the selection of wavelengths 
                         representative of the optically relevant constituents (ORCs) and 
                         calibration of values directly associated with the pigments and 
                         detritus plus colored dissolved organic material (CDM) absorption 
                         coefficients. The re-parametrized QAA eliminated the retrieval of 
                         negative values, commonly identified in other variants of QAA. The 
                         calibrated model generated a normalized root mean square error 
                         (NRMSE) of 21.88% and a mean absolute percentage error (MAPE) of 
                         28.27% for at(\λ), where the largest errors were found at 
                         412 nm and 620 nm. Estimated NRMSE for aCDM(\λ) was 18.86% 
                         with a MAPE of 31.17%. A NRMSE of 22.94% and a MAPE of 60.08% were 
                         obtained for a\φ(\λ). Estimated a\φ(665) and 
                         a\φ(709) was used to predict Chl-a concentration. 
                         a\φ(665) derived from QAA for Barra Bonita Hydroelectric 
                         Reservoir (QAA_BBHR) was able to predict Chl-a accurately, with a 
                         NRMSE of 11.3% and MAPE of 38.5%. The performance of the Chl-a 
                         model was comparable to some of the most widely used empirical 
                         algorithms such as 2-band, 3-band, and the normalized difference 
                         chlorophyll index (NDCI). The new QAA was parametrized based on 
                         the band configuration of MEdium Resolution Imaging Spectrometer 
                         (MERIS), Sentinel-2A and 3A and can be readily scaled-up for 
                         spatio-temporal monitoring of IOPs in tropical waters.",
                  doi = "10.1016/j.isprsjprs.2016.08.009",
                  url = "http://dx.doi.org/10.1016/j.isprsjprs.2016.08.009",
                 issn = "0924-2716",
             language = "en",
           targetfile = "watanabe_parametrization.pdf",
        urlaccessdate = "27 nov. 2020"