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

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

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th International Communications, signal processing and systems conference 2021 (CSPS 2021)
• 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: Jun 21, 2022
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• 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