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Estimation of chlorophyll concentration for environment monitoring in Scottish marine water.

Yan, Yijun; Zhang, Yixin; Ren, Jinchang; Hadjal, Madjid; Mckee, David; Kao, Fu-jen; Durrani, Tariq

Authors

Yixin Zhang

Madjid Hadjal

David Mckee

Fu-jen Kao

Tariq Durrani



Contributors

Qilian Liang
Editor

Wei Wang
Editor

Xin Liu
Editor

Zhenyu Na
Editor

Baoju Zhang
Editor

Abstract

Marine Scotland is tasked with reporting on the environmental status of Scottish marine waters, an enormous area of water extending from the shoreline to deep oceanic waters. As one of the most important variables, chlorophyll concentration (Chl) plays an important role in the seawater quality monitoring. Currently, the Chl observation is mostly done by expensive ship-based surveys that have very limited spatio-temporal coverage. Satellite based ocean colour remote sensing has the potential to significantly enhance monitoring capabilities but this opportunity has not been widely adopted by statutory reporting bodies across Europe due to concerns over satellite data quality. To break through this bottleneck, in this paper, we explore to implement advanced machine learning techniques to automatically estimate the Chl via the historic time series of ocean colour remote sensing data during from July 2002 to September 2019.

Citation

YAN, Y., ZHANG, Y., REN, J., HADJAL, M., MCKEE, D., KAO, F.-J., and DURRANI, T. 2022. Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 582-587. Available from: https://doi.org/10.1007/978-981-19-0390-8_71

Conference Name 10th International Communications, signal processing and systems conference 2021 (CSPS 2021)
Conference Location Baishishan, China
Start Date Aug 21, 2021
End Date Aug 22, 2021
Acceptance Date Jun 20, 2021
Online Publication Date Mar 30, 2022
Publication Date Dec 31, 2022
Deposit Date Jun 21, 2022
Publicly Available Date Mar 28, 2024
Publisher Springer
Pages 582-587
Series Title Lecture notes in electrical engineering (LNEE)
Series Number 878
Series ISSN 1876-1119; 1876-1100
Book Title Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems
ISBN 9789811903892
DOI https://doi.org/10.1007/978-981-19-0390-8_71
Keywords Environment monitoring; Scottish marine water; Chlorophyll; Multispectral remote sensing
Public URL https://rgu-repository.worktribe.com/output/1654343

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