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REVIEW article

Front. Mar. Sci.
Sec. Ocean Observation
Volume 12 - 2025 | doi: 10.3389/fmars.2025.1546289
This article is part of the Research Topic Remote Sensing Applications in Marine Ecology Monitoring and Target Sensing View all 6 articles

A Comprehensive Review of Remote Sensing Techniques for Monitoring Ulva prolifera Green Tides

Provisionally accepted
Xiaomeng Geng Xiaomeng Geng 1Li Huiru Li Huiru 1*Wang Le Wang Le 2*Sun Weidong Sun Weidong 3*Li Yize Li Yize 4*
  • 1 Hebei Normal University, Shijiazhuang, China
  • 2 Key Laboratory of Marine Ecological Monitoring and Restoration Technologies, MNR, Shanghai, China
  • 3 State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei Province, China
  • 4 Inner Mongolia University of Technology, Hohhot, Inner Mongolia Autonomous Region, China

The final, formatted version of the article will be published soon.

    In recent years, Ulva prolifera green tide, as a large-scale marine ecological phenomenon, has occurred frequently in coastal areas such as the Yellow Sea and the East China Sea, significantly affecting marine ecosystems and fishery resources. With the continuous advancement of remote sensing technologies, these technologies have become indispensable tools for monitoring Ulva prolifera green tides. This review provides a comprehensive overview of the advances in remote sensing band indices for detecting green tides, including spatiotemporal distribution analysis, area and biomass estimation, drift trajectory modeling, and investigations of their driving mechanisms. Additionally, it identifies the limitations and unresolved challenges in current approaches, such as constraints on data resolution, algorithmic biases, and environmental variability. The potential for integrating multi-source remote sensing data with marine environmental parameters and deep learning techniques is discussed, emphasizing their roles in improving the accuracy and reliability of monitoring and predicting Ulva prolifera green tides. This review aims to guide future research efforts and technological innovations in this field. also obstruct navigation channels, thereby posing serious threats to coastal fisheries, aquaculture, and tourism (Hu and He, 2008;Xing and Hu, 2016).Over the past two decades, the cultivation areas for Porphyra in China have expanded nearly fourfold, as shown in Figure 2. The Porphyra aquaculture rafts areas in the Subei Shoal (Lianyungang, Yancheng, and Nantong) are widely recognized as the primary breeding grounds for Ulva prolifera

    Keywords: Ulva prolifera green tide, Yellow Sea, East China Sea, remote sensing, deep learning

    Received: 16 Dec 2024; Accepted: 08 Jan 2025.

    Copyright: © 2025 Geng, Huiru, Le, Weidong and Yize. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Li Huiru, Hebei Normal University, Shijiazhuang, China
    Wang Le, Key Laboratory of Marine Ecological Monitoring and Restoration Technologies, MNR, Shanghai, China
    Sun Weidong, State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, Hubei Province, China
    Li Yize, Inner Mongolia University of Technology, Hohhot, Inner Mongolia Autonomous Region, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.