A Machine Learning-Based Assessment of Proxies and Drivers of Harmful Algal Blooms in the Western Lake Erie Basin Using Satellite Remote Sensing

A Machine Learning-Based Assessment of Proxies and Drivers of Harmful Algal Blooms in the Western Lake Erie Basin Using Satellite Remote Sensing

The western region of Lake Erie has been experiencing severe water-quality issues, mainly through the infestation of algal blooms, highlighting the urgent need for action. Understanding the drivers and the intricacies associated with algal bloom phenomena is important to develop effective water-qual...

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Bibliographic Details
Main Authors: Neha Joshi, Armeen Ghoorkhanian, Jongmin Park, Kaiguang Zhao, Sami Khanal
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
Subjects:
harmful algal blooms
Harmonized Landsat Sentinel-2
water quality
machine learning
Online Access:https://www.mdpi.com/2072-4292/17/13/2164
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