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The utility of both close-range and satellite remote sensing for assessing inland water quality was examined in the Iowa Great Lakes. The water quality of this system is of considerable interest because of its status as an environmental, recreational, and therefore, economic resource. The broad range of optical conditions present in the lakes and the wealth of literature on the system make it an ideal environment for water quality remote sensing research. The goal of this research was to survey the water quality of the Iowa Great Lakes via remote sensing, evaluate different predictive algorithms, and map the distribution of algal biomass. In situ sampling was carried out on Spirit, West Okoboji, and East Okoboji lakes, concurrent with a SPOT-2 satellite overpass, August 13, 1997. A total of 26 sample sites were visited. Measurements included chlorophyll a, turbidity, vertical attenuation, hyperspectral radiance/reflectance, and GPS. Aerial photographs were taken later in order to illustrate the spatial characteristics of various aquatic features. Empirical relationships between chlorophyll and both close-range (hyperspectral) and satellite (broad-band) data, were evaluated using correlation and regression techniques. Results suggest that low chlorophyll concentrations are difficult to estimate, while moderate to high biomass levels can be accurately modeled using either closerange or satellite data. The near-infrared portion of the optical spectrum proved the single most useful spectral region for estimating chlorophyll concentration. Due to their ability to correct for nonalgal scattering, the NIR:Red ratio (r2 = 0.997) and the Baseline Sum (r2 = 0.998) algorithms, proved the most effective for estimating chlorophyll In hypereutrophic East Okoboji Lake. Chlorophyll a maps were developed by applying an algorithm based on nearinfrared band radiance magnitude (r2 = 0.833) to the SPOT imagery. The distribution of algal biomass is predominantly homogeneous in West Okoboji and Spirit lakes, but extremely patchy in Lake East Okoboji. This spatial heterogeneity of water quality constituents may be a significant source of error for monitoring programs based solely on point sampling.
Advisor: Donald C. Rundquist