Development of the Digital Twin of Estuarine and Coastal System (DTEC)
编号:1455 访问权限:仅限参会人 更新:2025-01-04 11:52:17 浏览:199次 口头报告

报告开始:2025年01月15日 14:00(Asia/Shanghai)

报告时间:15min

所在会场:[S32] Session 32-Digital Twins of the Ocean (DTO) and Its Applications [S32-1] Digital Twins of the Ocean (DTO) and Its Applications

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摘要

The Digital Twin of Estuarine and Coastal System (DTEC) is developed to address the growing demand for advanced tools in managing and protecting critical coastal areas. With over 50% of the global population and 80% of metropolitan areas located in estuaries and coasts, these regions are both economic powerhouses and biodiversity hotspots. However, they face significant threats from increasing human activity, climate change, and environmental degradation. Current observational and modeling tools suffer from fragmented data streams, lack of real-time monitoring, and limited predictive accuracy, making sustainable management challenging.

DTEC integrates multi-source data, AI-driven models, and real-time monitoring to create a comprehensive digital representation of coastal environments. This digital twin enhances forecasting, early warning, disaster prevention, and sustainable management capabilities. By leveraging advanced data assimilation techniques and AI models, DTEC significantly improves the understanding of complex estuarine processes, helping stakeholders address environmental and socio-economic challenges. The system also includes intelligent decision support tools that provide a robust foundation for data-driven policymaking and sustainable coastal development.

Recent advancements in DTEC include the incorporation of AI-driven technologies, such as the YOLO algorithm for real-time hydrological and geomorphological analysis, improving the accuracy of grain size recognition. AI-based remote sensing, using advanced neural networks, enhances wetland classification and biomass estimation. Predictive models powered by LSTM and CNN are now utilized for wave height and storm surge forecasts, providing more accurate and timely predictions. Additionally, a novel user-driven AI visualization interface allows for better analysis of large-scale datasets, aiding in disaster prevention and ecological management decisions. These developments establish DTEC as a leading platform for sustainable coastal development, offering enhanced real-time monitoring, predictive capabilities, and intelligent decision-making support.

关键词
digital twin, estuary, coast
报告人
Zhong Peng
Professor East China Normal University

稿件作者
Zhong Peng East China Normal University
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重要日期
  • 会议日期

    01月13日

    2025

    01月17日

    2025

  • 09月27日 2024

    初稿截稿日期

  • 01月17日 2025

    注册截止日期

主办单位
State Key Laboratory of Marine Environmental Science, Xiamen University
承办单位
State Key Laboratory of Marine Environmental Science, Xiamen University
Department of Earth Sciences, National Natural Science Foundation of China
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