@Article{MartinsBaCaJoLoNo:2017:AsAtCo,
               author = "Martins, Vitor Souza and Barbosa, Cl{\'a}udio Clemente Faria and 
                         Carvalho, Lino Augusto Sander de and Jorge, Daniel Schaffer 
                         Ferreira 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 = "Assessment of atmospheric correction methods for sentinel-2 MSI 
                         images applied to Amazon floodplain lakes",
              journal = "Remote Sensing",
                 year = "2017",
               volume = "9",
               number = "4",
                month = "Apr.",
             keywords = "Adjacency correction, Amazon inland water, Atmospheric correction, 
                         MAIAC aerosol product, MODIS atmospheric product, TOA 
                         simulation.",
             abstract = "Satellite data provide the only viable means for extensive 
                         monitoring of remote and large freshwater systems, such as the 
                         Amazon floodplain lakes. However, an accurate atmospheric 
                         correction is required to retrieve water constituents based on 
                         surface water reflectance (RW). In this paper, we assessed three 
                         atmospheric correction methods (Second Simulation of a Satellite 
                         Signal in the Solar Spectrum (6SV), ACOLITE and Sen2Cor) applied 
                         to an image acquired by the MultiSpectral Instrument (MSI) 
                         on-board of the European Space Agency's Sentinel-2A platform using 
                         concurrent in-situ measurements over four Amazon floodplain lakes 
                         in Brazil. In addition, we evaluated the correction of forest 
                         adjacency effects based on the linear spectral unmixing model, and 
                         performed a temporal evaluation of atmospheric constituents from 
                         Multi-Angle Implementation of Atmospheric Correction (MAIAC) 
                         products. The validation of MAIAC aerosol optical depth (AOD) 
                         indicated satisfactory retrievals over the Amazon region, with a 
                         correlation coefficient (R) of ~0.7 and 0.85 for Terra and Aqua 
                         products, respectively. The seasonal distribution of the cloud 
                         cover and AOD revealed a contrast between the first and second 
                         half of the year in the study area. Furthermore, simulation of 
                         top-of-atmosphere (TOA) reflectance showed a critical contribution 
                         of atmospheric effects (>50%) to all spectral bands, especially 
                         the deep blue (92%-96%) and blue (84%-92%) bands. The atmospheric 
                         correction results of the visible bands illustrate the limitation 
                         of the methods over dark lakes (RW < 1%), and better match of the 
                         RW shape compared with in-situ measurements over turbid lakes, 
                         although the accuracy varied depending on the spectral bands and 
                         methods. Particularly above 705 nm, RW was highly affected by 
                         Amazon forest adjacency, and the proposed adjacency effect 
                         correction minimized the spectral distortions in RW (RMSE < 
                         0.006). Finally, an extensive validation of the methods is 
                         required for distinct inland water types and atmospheric 
                         conditions.",
                  doi = "10.3390/rs9040322",
                  url = "http://dx.doi.org/10.3390/rs9040322",
                 issn = "2072-4292",
             language = "en",
           targetfile = "martins-assessment.pdf",
        urlaccessdate = "18 abr. 2024"
}