@InProceedings{JorgeBaAfCaLoNo:2018:StCaAm,
               author = "Jorge, Daniel Schaffer Ferreira and Barbosa, Cl{\'a}udio Clemente 
                         Faria and Affonso, Adriana and Carvalho, Lino Augusto Sander de 
                         and Lobo, Felipe de Lucia and Novo, Evlyn M{\'a}rcia Le{\~a}o de 
                         Moraes",
          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)}",
                title = "Challenges in applying semi-analytical algorithms on optically 
                         complex waters: a study case for Amazon floodplain lakes",
                 year = "2018",
         organization = "Ocean Sciences Meeting",
             abstract = "Developing precise algorithms to retrieve optical information from 
                         inland waters is critical to increase the applicability of remote 
                         sensing data for monitoring purposes. Although semi-analytical 
                         (SA) algorithms were developed for ocean waters, they have been 
                         adapted and applied for inland and coastal waters with relatively 
                         success, but for extremely complex waters validation is yet to be 
                         achieved. The objective of this study is to assess the potential 
                         of SA algorithms applied to Amazon lakes, which are very dynamic, 
                         with high variability of CDOM, detritus and phytoplankton 
                         concentration. In order to achieve this, in situ optical data was 
                         obtained during five missions between 2015 and 2016, with a total 
                         of 102 sampling points. Two SA algorithms design for Amazonian 
                         lakes were tested: Spectral Optimization Algorithm (SOA); and 
                         Quasi-Analytical Algorithm (QAA). Each algorithm was calibrated, 
                         using both the original structure and changes proposed for 
                         optically complex waters. The algorithms were initially tested for 
                         the whole dataset with not satisfactory results. To improve the 
                         algorithm performance, the dataset was further divided in dark 
                         lakes (9.5 > TSS > 5.2; 6.4 > CDOM(420 nm) > 2.5 m-1) and bright 
                         lakes (25.9 > TSS > 6.8; 2.6 > CDOM(420 nm) > 2.1 m-1), based on 
                         the Rrs spectrum. Preliminary results, of this ongoing research, 
                         showed that total absorption spectra derived from SOA, when 
                         compared to in situ measurements, presented a high agreement in 
                         the blue region of the spectra (significant at p < 0.05), whereas 
                         for the red part of the spectrum a clear correlation couldnt be 
                         observed (p > 0.05). For the QAA algorithm, high uncertainty was 
                         observed in the estimation of backscattering (in situ from 0.01 to 
                         1.5 m-1 ) during the calibration phase, resulting in error 
                         propagation throughout the modeling. Although the authors tested 
                         both exponential and logarithmic equations to quantify the 
                         backscattering, the results were poor for all the lakes. 
                         Therefore, the initial results showed that the SA algorithms 
                         designed for Case-1 and Case-2 need to be restructured and 
                         validated to be successfully applied to optically complex waters, 
                         such those from Amazon floodplain lakes.",
  conference-location = "Portland, Oregon, USA",
      conference-year = "11-16 Feb.",
             language = "en",
        urlaccessdate = "28 abr. 2024"
}