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@Article{PahlevanMBSAABBBBGGFHHIKLLMMOOPPRCSSSSSTTVW:2021:GlAsAt,
               author = "Pahlevan, Nima and Mangin, Antoine and Balasubramanian, 
                         Sundarabalan V. and Smith, Brandon and Alikas, Krista and Arai, 
                         Kohei and Barbosa, Cl{\'a}udio Clemente Faria and B{\'e}langer, 
                         Simon and Binding, Caren and Bresciani, Mariano and Giardino, 
                         Cl{\'a}udia and Gurlin, Daniela and Fan, Yongzhen and Harmel, 
                         Tristan and Hunter, Peter and Ishikaza, Joji and Kratzer, Susanne 
                         and Lehmann, Moritz K. and Ligi, Martin and Ma, Ronghua and 
                         Martin-Lauzer, Fran{\c{c}}ois-R{\'e}gis and Olmanson, Leif and 
                         Oppelt, Natascha and Pan, Yangun and Peters, Steef and Reynauld, 
                         Nathalie and Carvalho, Lino Augusto Sander de and Simis, Stefan 
                         and Spyrakos, Evangelos and Steinmetz, Fran{\c{c}}ois and 
                         Stelzer, Kersint and Sterckx, Sindy and Tormos, Thierry and Tyler, 
                         Andrew and Vanhellemont, Quinten and Warrren, Mark",
          affiliation = "{NASA Goddard Space Flight Center} and ACRI-ST and {Geosensing and 
                         Imaging Solution Consultancy} and {NASA Goddard Space Flight 
                         Center} and {University of Tartu} and {Saga University} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universit{\'e} du Qu{\'e}bec} and {Environment and Climate 
                         Change Canada} and {National Research Council of Italy} and 
                         {National Research Council of Italy} and {Wisconsin Department of 
                         Natural Resources} and {Stevens Institute of Technology} and 
                         {G{\'e}osciences Environment Toulouse (GET)} and {University of 
                         Stirling} and {Nagoya University} and {Stockholm University} and 
                         {University of Waikato} and {University of Tartu} and {Chinese 
                         Academy of Science} and ACRI-ST and {University of Minnesota} and 
                         {Kiel University} and {Universit{\'e} du Qu{\'e}bec} and {Water 
                         Insight} and {UR RECOVER} and {Universidade Federal do Rio de 
                         Janeiro (UFRJ)} and {Plymouth Marine Laboratory} and {University 
                         of Stirling} and Euratechnologies and {Brockmann Consult GmbH} and 
                         {Flemish Institute for Technological Research (VITO)} and 
                         {Unit{\'e} ECosyst{\`e}mes LAcustres} and {University of 
                         Stirling} and {Royal Belgian Institute of Natural Sciences 
                         (RBINS)} and {Plymouth Marine Laboratory}",
                title = "ACIX-Aqua: A global assessment of atmospheric correction methods 
                         for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal 
                         waters",
              journal = "Remote Sensing of Environment",
                 year = "2021",
               volume = "258",
                pages = "e112366",
                month = "June",
             abstract = "Atmospheric correction over inland and coastal waters is one of 
                         the major remaining challenges in aquatic remote sensing, often 
                         hindering the quantitative retrieval of biogeochemical variables 
                         and analysis of their spatial and temporal variability within 
                         aquatic environments. The Atmospheric Correction Intercomparison 
                         Exercise (ACIX-Aqua), a joint NASA ESA activity, was initiated to 
                         enable a thorough evaluation of eight state-of-the-art atmospheric 
                         correction (AC) processors available for Landsat-8 and Sentinel-2 
                         data processing. Over 1000 radiometric matchups from both 
                         freshwaters (rivers, lakes, reservoirs) and coastal waters were 
                         utilized to examine the quality of derived aquatic reflectances 
                         (\ρ\̂w). This dataset originated from two sources: 
                         Data gathered from the international scientific community 
                         (henceforth called Community Validation Database, CVD), which 
                         captured predominantly inland water observations, and the Ocean 
                         Color component of AERONET measurements (AERONET-OC), representing 
                         primarily coastal ocean environments. This volume of data 
                         permitted the evaluation of the AC processors individually (using 
                         all the matchups) and comparatively (across seven different 
                         Optical Water Types, OWTs) using common matchups. We found that 
                         the performance of the AC processors differed for CVD and 
                         AERONET-OC matchups, likely reflecting inherent variability in 
                         aquatic and atmospheric properties between the two datasets. For 
                         the former, the median errors in \ρ\̂w560 and 
                         \ρ\̂w664 were found to range from 20 to 30% for 
                         best-performing processors. Using the AERONET-OC matchups, our 
                         performance assessments showed that median errors within the 1530% 
                         range in these spectral bands may be achieved. The largest 
                         uncertainties were associated with the blue bands (25 to 60%) for 
                         best-performing processors considering both CVD and AERONET-OC 
                         assessments. We further assessed uncertainty propagation to the 
                         downstream products such as near-surface concentration of 
                         chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using 
                         satellite matchups from the CVD along with in situ Chla and TSS, 
                         we found that 2030% uncertainties in 
                         \ρ\̂w490\≤\λ\≤743nm yielded 2570% 
                         uncertainties in derived Chla and TSS products for top-performing 
                         AC processors. We summarize our results using performance matrices 
                         guiding the satellite user community through the OWT-specific 
                         relative performance of AC processors. Our analysis stresses the 
                         need for better representation of aerosols, particularly absorbing 
                         ones, and improvements in corrections for sky- (or sun-) glint and 
                         adjacency effects, in order to achieve higher quality downstream 
                         products in freshwater and coastal ecosystems.",
                  doi = "10.1016/j.rse.2021.112366",
                  url = "http://dx.doi.org/10.1016/j.rse.2021.112366",
                 issn = "0034-4257",
             language = "en",
           targetfile = "pahlevan_acix.pdf",
        urlaccessdate = "28 mar. 2024"
}


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