Remote sensing for regional assessment and analysis of Minnesota lake and river water quality

Abstract

Beginning soon after the launch of the first Landsat satellite, researchers began investigating the use of Landsat imagery to monitor the water quality of our lakes and coastlines. The earliest use of Landsat imagery was for simple qualitative observations which included locating and mapping pollution and pollution plumes. Shortly thereafter, field measurements of water quality were correlated with Landsat data and later these correlations were used for quantitative assessment of water quality (e.g., turbidity, chlorophyll and water clarity). This dissertation expands on this earlier work and describes results of research to develop and use remote sensing tools for regional water quality assessment to improve the understanding and management of Minnesota's lakes and rivers. It includes four major components. First, a 20-year, 1985-2005, comprehensive water clarity database for more than 10,500 lakes at approximately five-year intervals for the time period 1985-2005, which includes almost 100,000 individual estimates of lake water clarity, was compiled and evaluated. Second, the results of a statistical analysis of the Landsat database for geospatial and temporal trends of water clarity over the 20-year period, as well as trends related to land cover/use and lake morphometry, are reported. Third, the advantages of improved spectral and temporal resolution and disadvantages of the lower spatial resolution of the global MODIS and MERIS systems are evaluated for regional-scale measurements of lake water clarity and chlorophyll of large lakes in Minnesota and compared with Landsat. Finally, aerial hyperspectral spectrometers were used to collect imagery with high spatial and spectral resolution for use in identifying, measuring and mapping optically related water quality characteristics of major rivers in Minnesota for three time periods that represent different water quality and flow regimes.