Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques

Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques

Chlorophyll-a (Chl-a) is a critical biological indicator of the eutrophic state of water bodies, emphasizing the importance of its detailed characterization and continuous monitoring. This study evaluated the performance of 10 widely used Machine Learning (ML) algorithms in deriving the spatiotempor...

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Bibliographic Details
Main Authors: Mohammad Shakiul Islam, Padmanava Dash, Abduselam M. Nur, Hafez Ahmad, Rajendra M. Panda, Jessica S. Wolfe, Gray Turnage, Lee Hathcock, Gary D. Chesser, Jr, Robert J. Moorhead
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Ecological Informatics
Subjects:
Chlorophyll-a
Uncrewed aircraft systems
Autonomous surface vessel
Machine learning algorithm
Feature selection techniques
Online Access:http://www.sciencedirect.com/science/article/pii/S1574954124004965
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