SPATIAL PATTERNS OF ALGAL BLOOMS IN LAKE BLOOMINGTON AND EVERGREEN LAKE USING FIELD OBSERVATIONS AND REMOTE SENSING
This project explores the effects of algal blooms in water and the environment using remote sensing data to monitor algal bloom occurrence and to develop methods that are transferable and will enable the determination of algal bloom occurrence at other locations. Monitoring of lakes using satellite remote sensing data is useful in estimating and detecting water quality problems that would have gone undetected in lakes. We are also collecting water samples, from selected locations on the lakes, to test for various water properties such as nitrate, phosphate, chlorophyll a, etc. A function derived from regression analysis conducted alongside with models/maps created will be used to predict water quality of the other locations of the lake not selected. Results have shown that blooms occur at different times of the year in each lake e.g. August for Evergreen Lake, October for Lake Bloomington. Using satellite image reflectance data from Landsat 8 images, we expect to see spatial patterns in water quality.