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@Article{KuhnVWLSKRSCSVPB:2019:PeLaSe,
               author = "Kuhn, Catherine and Val{\'e}rio, Aline de Matos and Ward, Nick 
                         and Loken, Luke and Sawakuchi, Henrique Oliveira and Kampel, 
                         Milton and Richey, Jeffrey and Stadler, Philipp and Crawford, John 
                         and Striegl, Rob and Vermote, Eric and Pahlevan, Nima and Butman, 
                         David",
          affiliation = "{University of Washington} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Pacific Northwest National Laboratory} and 
                         {U.S. Geological Survey} and {Universidade de S{\~a}o Paulo 
                         (USP)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {University of Washington} and TU Wien, Centre for Water Resource 
                         Systems and {U.S. Geological Survey} and {U.S. Geological Survey} 
                         and {NASA Goddard Space Flight Cente} and {NASA Goddard Space 
                         Flight Cente} and {University of Washington}",
                title = "Performance of Landsat-8 and Sentinel-2 surface reflectance 
                         products for river remote sensing retrievals of chlorophyll-a and 
                         turbidity",
              journal = "Remote Sensing of Environment",
                 year = "2019",
               volume = "224",
                pages = "104--118",
                month = "Apr.",
             keywords = "Atmospheric correction, Ocean color, Landsat-8, Sentinel-2, 
                         Mississippi River, Amazon River, Columbia River, Turbid waters, 
                         Inland waters, Remote Sensing.",
             abstract = "Rivers and other freshwater systems play a crucial role in 
                         ecosystems, industry, transportation and agriculture. Despite the 
                         >40\ years of inland water observations made possible by 
                         optical remote sensing, a standardized reflectance product for 
                         inland waters is yet forthcoming. The aim of this work is to 
                         compare the standard USGS land surface reflectance product to two 
                         Landsat-8 and Sentinel-2 aquatic remote sensing reflectance 
                         products over the Amazon, Columbia and Mississippi rivers. 
                         Landsat-8 reflectance products from all three routines are then 
                         evaluated for their comparative performance in retrieving 
                         chlorophyll-a and turbidity in reference to ship-borne, underway 
                         in situ validation measurements. The land surface product shows 
                         the best agreement (4% Mean Absolute Percent Difference) with 
                         field measurements of radiometry collected on the Amazon River and 
                         generates 36% higher reflectance values in the visible bands 
                         compared to aquatic methods (ACOLITE and SeaDAS) with larger 
                         differences between land and aquatic products observed in 
                         Sentinel-2 (0.01\ sr\−1) compared to Landsat-8 
                         (0.001\ sr\−1). Choice of atmospheric correction 
                         routine can bias Landsat-8 retrievals of chlorophyll-a and 
                         turbidity by as much as 59% and 35% respectively. Using a more 
                         restrictive time window for matching in situ and satellite imagery 
                         can reduce differences by 531% depending on correction technique. 
                         This work highlights the challenges of satellite retrievals over 
                         rivers and underscores the need for future optical and 
                         biogeochemical research aimed at improving our understanding of 
                         the absorbing and scattering properties of river water and their 
                         relationships to remote sensing reflectance.",
                  doi = "10.1016/j.rse.2019.01.023",
                  url = "http://dx.doi.org/10.1016/j.rse.2019.01.023",
                 issn = "0034-4257",
             language = "en",
           targetfile = "kuhn_perfomance.pdf",
        urlaccessdate = "04 dez. 2020"
}


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