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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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Principais autores: 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: Artigo
Sprog:Inglês
Udgivet: Elsevier 2025-03-01
Serier:Ecological Informatics
Fag:
Chlorophyll-a
Uncrewed aircraft systems
Autonomous surface vessel
Machine learning algorithm
Feature selection techniques
Online adgang:http://www.sciencedirect.com/science/article/pii/S1574954124004965
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