Evaluation of remote sensing light attenuation algorithms in the Great Lakes

Session: Remote Sensing, Visualization, and Spatial Data Applications for the Great Lakes (1)

Karl Bosse, Michigan Tech Research Inst., [email protected]
Mike Sayers, Michigan Tech. Research Inst., [email protected]
Robert Shuchman, Michigan Technological University, [email protected]
Steve Ruberg, NOAA - GLERL, [email protected]
George Leshkevich, Great Lakes Env. Research Lab, NOAA, [email protected]
Dack Stuart, CIGLR, University of Michigan, [email protected]

Abstract

Because the amount of light available in the water column is related to water clarity and primary production, much time has been spent studying its spatial and temporal trends. In situ approaches to measure light attenuation tend to be most accurate, but the cost and time constraints limit the ability to get widespread coverage. Algorithms have been developed to estimate the diffuse attenuation coefficent (Kd) from satellite remote sensing observations which allows for a more complete understanding of the spatial and temporal variability. However, validation efforts for these algorithms in inland waters like the Great Lakes have been limited. We have aggregated radiometric profiles from multiple sources collected throughout the Great Lakes from 2004 through 2018 in order to generate a robust dataset of in situ Kd measurements. These measurements were compared to Kd estimates from multiple remote sensing algorithms in order to assess the performance of these algorithms in the Great Lakes. Further, Kd estimates were derived from in situ surface reflectance measurements in order to assess whether the relationships between reflectance and attenuation that have been used for satellite remote sensing hold true in the Great Lakes.