Keywords

Remote sensing, harmful algal blooms, geospatial analysis, environmental science

Mentor

Nicholas Preville

Abstract

Great Lakes basins and inland waterways experience increased harmful algal bloom (HAB) production as a result of eutrophication– excess nutrient loading into waterways from agriculture and urbanization. Muskegon Lake, an estuary located on the eastern coast of Lake Michigan, was classified as a Great Lakes Area of Concern in 1985 due to severe HABs from several impairments including agricultural runoff and industrial waste dumping. Because of the ecosystem and human health threats posed by HABs such as wildlife and human illness and drinking water contamination, monitoring the abundance of HABs in inland waterways is imperative. The goal of this study was to evaluate the application and validity of remote sensing cyanobacteria abundance in Muskegon Lake using Sentinel-3 Ocean and Land Color Instrument (OLCI) satellite imagery from 2016-2021. Results show that the cyanobacteria quantification algorithm calculated high cell densities up to 1.25 million compared to in situ measurements up to 25,000 from a phycocyanin probe on the Muskegon Lake Buoy Observatory. However, remotely sensed cyanobacteria densities follow the same growth and die-off trends as calculated by the Buoy phycocyanin probe. Moreover, the results of this study display that remote sensing cyanobacteria HABs can supplement field data in flagging high HAB days for public health monitoring as well as documenting historical growth trends.

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