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Remote sensing

University of Massachusetts Amherst

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Using Remote Sensing And Environmental Precursors To Detect And Predict Cyanobacteria Harmful Algal Blooms In Northeastern Us Waterbodies, Amanda Craver Apr 2021

Using Remote Sensing And Environmental Precursors To Detect And Predict Cyanobacteria Harmful Algal Blooms In Northeastern Us Waterbodies, Amanda Craver

Environmental & Water Resources Engineering Masters Projects

Cyanobacteria harmful algal blooms (cyanoHABs) are a global problem with human health, environmental, and economic concerns. The severity and frequency of toxic cyanoHABs are expected to increase with climate change. Remote sensing has proven to be a useful tool in monitoring cyanoHABs. This study uses remote sensing observations from Sentinel-3Ocean Land Color Imager (OLCI)combined with the Spectral Shape Algorithm (SSA) to detect the presence of cyanobacteria in numerous waterbodies throughout the Northeast United States over 2016to 2020. The ACOLITE processor was used for the atmospheric correction of the Sentinel-3 OLCI data, as it has been shown to provide more accurate …