Water Properties in the Great Lakes from Satellite Ocean Color Measurements

Satellite remote sensing data can be used synoptically to monitor water properties in inland lakes as useful monitoring and management tools for understanding biological and ecological processes and phenomena. In this presentation, effects of ice contamination on satellite-derived ocean color products in the Great Lakes are studied and a regional ice-detection algorithm is developed for the Moderated Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color data in the Great Lakes. Results show that satellite-derived ocean color products have significantly errors in ice-contaminated pixels using the standard ice masking method in the Great Lakes. The new proposed ice-detection method works well for MODIS and VIIRS data in identifying most of ice-contaminated pixels in the Great Lakes. Furthermore, based on a relationship of the water turbidity with the diffuse attenuation coefficient for photosynthetically available radiation (PAR), K_d(PAR), a regional water turbidity algorithm for satellite application has been developed and validated for the Great Lakes. With the new ice-detection method, MODIS- and VIIRS-measured ocean color products and water turbidity data in the Great Lakes have been generated and used for characterizing water properties in the region, showing apparent seasonal and interannual variability. The satellite-derived water property data show highly turbid waters in Lake Erie, as well as along some coastal areas in those lakes, compared to the rest of lakes, possibly due to shallow bathymetry in these regions.