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A novel method to estimate the 3D chlorophyll a distribution in the South China Sea surface waters using hydrometeorological parameters

Abstract Chlorophyll a (Chl-a) is a key indicator of marine ecosystems, and certain hydro-meteorological parameters (HMPs) are highly correlated with its fluctuations. Here, relevant and accessible HMPs were used as inputs, combined with machine learning (ML) algorithms for estimating 3D Chl-a in th...

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Uloženo v:
Hlavní autoři: Yuanning Zheng, Cai Li, Wen Zhou, Zhantang Xu, Xianqing Zhang, Wenxi Cao, Zeming Yang, Changjian Liu
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Portfolio 2024-10-01
Edice:Scientific Reports
Témata:
Water quality monitoring
Machine learning
Chlorophyll a
Hydro-meteorology
South China Sea
On-line přístup:https://doi.org/10.1038/s41598-024-76748-5
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