Satellite remote sensing monitoring of chlorophyll <i>a</i> mass concentration in a typical marine ranching area of Gouqi Island

Meng Jiayu; Wang Shengqiang; Sun Deyong; Jiang Xinyi; Zhang Xiumei; Lang Shuyan; Jia Yongjun

doi:10.12284/hyxb2025138

Volume 47 Issue 11

Nov. 2025

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Meng Jiayu，Wang Shengqiang，Sun Deyong, et al. Satellite remote sensing monitoring of chlorophyll a mass concentration in a typical marine ranching area of Gouqi Island[J]. Haiyang Xuebao，2025, 47(11)：141–153 doi: 10.12284/hyxb2025138

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Satellite remote sensing monitoring of chlorophyll a mass concentration in a typical marine ranching area of Gouqi Island

doi: 10.12284/hyxb2025138

Meng Jiayu^{1, 2
,},
Wang Shengqiang^{1, 2, 3
,
,},
Sun Deyong^{1, 2, 3},
Jiang Xinyi^{1, 2},
Zhang Xiumei⁴,
Lang Shuyan^{3, 5},
Jia Yongjun^{3, 5}

1.
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
3.
Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China
4.
Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
5.
National Satellite Ocean Application Service, Beijing 100081, China

Received Date: 2025-07-15
Rev Recd Date: 2025-10-10

Available Online: 2025-10-22

Publish Date: 2025-11-30

Abstract

Abstract

Water quality monitoring in marine ranching areas is of vital importance for their high-quality and sustainable development. Chlorophyll a (Chl a), an important indicator of phytoplankton biomass and water eutrophication, plays a key role in environmental assessment and risk management. Satellite remote sensing, characterized by rapid observation and wide spatiotemporal coverage, offers significant advantages. However, dedicated remote sensing products for marine ranching areas remain lacking, and aquaculture facilities can interfere with satellite signals, introducing errors in the remote sensing inversion of Chl a mass concentration. Using the Gouqi Island marine ranching area (a mussel aquaculture ranching area) in Shengsi, Zhejiang Province, as a case study, Chl a mass concentration inversion models for Landsat8 OLI images were constructed based on in situ data acquired during multiple cruises. The influence of aquaculture facilities on remote sensing reflectance was analyzed and effectively corrected. Validation results demonstrated the good performance of the inversion model. Using the corrected reflectance data, high-precision Chl a mass concentration products were retrieved for the mussel aquaculture ranching area and adjacent waters, and their spatiotemporal variations and potential influencing factors were examined. This study provides methodological support and a technical foundation for high-precision remote sensing monitoring of Chl a mass concentration in mussel aquaculture ranching areas.

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