@InProceedings{KuhnVWLSKRSCSVPB:2018:AsAtCo,
               author = "Kuhn, Catherine and Val{\'e}rio, Aline de Matos and Ward, 
                         Nicholas D. and Loken, Luke C. and Sawakuchi, Henrique Oliveira 
                         and Kampel, Milton and Richey, Jeffrey E. and Stadler, Philipp and 
                         Crawford, John and Striegl, Robert G. and Vermote, Eric and 
                         Pahlevan, Nima and Butman, David E.",
          affiliation = "{University of Washington Seattle Campus} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {Pacific Northwest National 
                         Laboratory} and {University of California-Davis} and {Universidade 
                         de S{\~a}o Paulo (USP)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {University of Washington} and {Vienna 
                         Technical University} and UW-Madison and {USGS WRD} and {NASA 
                         Goddard Space Flight Center} and GSFC and {University of 
                         Washington}",
                title = "Assessment of atmospheric correction methods for Landsat-8 and 
                         sentinel-2 over Large Rivers",
                 year = "2018",
         organization = "AGU Fall Meeting",
             abstract = "The process of atmospheric correction removes effects of the 
                         atmosphere from satellite images to provide accurate estimates of 
                         reflectance at the Earths surface. The resulting reflectance forms 
                         the basis for bio-optical models of water quality parameters such 
                         as chlorophyll-a and turbidity that are relevant to global 
                         biogeochemical cycles and water management. Atmospheric correction 
                         routines vary by sensor and application but remain widely untested 
                         over large river systems. Here we assess the consequence of 
                         atmospheric correction choice on derived water quality products 
                         over three large rivers: the Amazon, Columbia and Mississippi 
                         Rivers. We show the Landsat-8 Surface Reflectance Code (LaSRC) 
                         produces reflectance estimates similar to field measurements 
                         despite being a technique derived for terrestrial applications. We 
                         also found that specialized aquatic correction routines were in 
                         better agreement with each other than with the land-based LaSRC 
                         technique and that disagreements were more exaggerated for 
                         Sentinel-2 data compared to Landsat-8. The resulting maps of key 
                         water quality variables show mean absolute errors ranging from 15 
                         -30% as a result of model choice. Our results demonstrate how 
                         choice of atmospheric correction method generates differences in 
                         surface reflectance that propagate through to estimates of water 
                         quality. This work lays the foundation for more intensive 
                         field-based measurements of optical properties relevant to the 
                         remote sensing of rivers and other inland water bodies.",
  conference-location = "Washington, D. C.",
      conference-year = "10-14 dec.",
             language = "en",
           targetfile = "kuhn_assessment.pdf",
        urlaccessdate = "27 abr. 2024"
}