Digital twin (DT)

Digital twin (DT): is a digital model of an intended or actual real-world physical product, system, or process that serves as the effectively indistinguishable digital counterpart of it for practical purposes, such as simulation, integration, testing, monitoring, and maintenance (Moi, Cibicik, and Rolvåg 2020; Haag and Anderl 2018; Boschert and Rosen 2016; Wikipedia 2024a).

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基于数字孪生的现实条件海平面上升模拟

基于数字孪生的现实条件海平面上升模拟

Source: ©SpaceData Inc.

Translated by Dr. Mengyi Jin

数字孪生技术正越来越多地应用于模拟海平面上升所带来的影响，为城市规划、海岸管理和灾害应对等领域的决策者提供了宝贵的工具。这些虚拟模型整合了包括地理空间影像、人工智能和环境监测系统等不同来源的实时数据，可以详细模拟海平面上升对特定区域产生的影响。

通过准确绘制当前的土地覆盖特征，并不断用新数据更新这些模型，数字孪生使研究人员和政府部门能够在不同的气候变化条件下对未来的情景进行预测。这有助于识别脆弱区域、规划基础防护设施以及优化疏散策略。例如，高分辨率地理空间数据可以显示哪些区域面临洪水风险，而由人工智能驱动的模拟则可以预测海平面上升可能对当地生态系统和城市环境产生的长期影响。

通过将海平面上升纳入数字孪生模拟，城市规划者和环境科学家可以充分了解其对沿海地区的长期影响，从而为气候变化带来的挑战做好更加充分的准备。这项技术对于直观呈现和科学规划适应性应对措施，从而减缓海平面上升可能造成的损害具有重要意义。

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An overview of digital twins in water systems

An overview of digital twins in water systems

overview of digital twins in water systems
Short summary: Digital twin (DT) technology for water systems is currently blooming. How are DT applied in water systems and why did they become so popular? In this article, the framework of DT and crucial technologies to build them such as space-based satellites, modern communication technologies, artificial intelligence, etc. are revealed to present how DT functionality is implemented. Application scenarios of DT from global to regional are shown with typical examples for modeling the global water cycle, regional floods, and urban water supply systems. Though DT offers a valuable solution in the context of water systems, attention needs to be given to accuracy, interoperability and data security of DT. DT can be smart systems, helping in comprehensive analysis to support decision making.
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Digital Twin solution for realistic sea level rise simulation

Digital Twin solution for realistic sea level rise simulation

Source: ©SpaceData Inc.

Digital twin technology is increasingly being used to simulate the effects of sea level rise, providing valuable tools for decision-makers in areas such as urban planning, coastal management, and disaster preparedness. These virtual models integrate real-time data from various sources, including geospatial imagery, AI, and environmental monitoring systems, to create detailed simulations of how rising sea levels could impact specific regions. 

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Stakeholder

University of Stirling

University of Stirling

Logo Univserity of Stirling

The University of Stirling was founded by Royal Charter in 1967 as the first genuinely new university in Scotland for over 400 years and embraces its role as an innovative, intellectual and cultural institution. A research-led university with an international reputation for high-quality research directly relevant to society’s needs, Stirling aims to be at the forefront of research and learning that helps to improve lives. The University works closely with its stakeholders in policy, practice and industry to facilitate this and enhance the relevance and impact of its research.

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Institute of Ionosphere

Institute of Ionosphere

Logo of the Institute of Ionosphere

The Institute of Ionosphere is a national scientific research institution operating under the Aerospace Committee of the Ministry of Digital Development, Innovation and Aerospace Industry of the Republic of Kazakhstan. Since its foundation in 1961, the Institute has evolved into a multidisciplinary center focused on ionospheric physics, atmospheric science, geospatial technologies, and environmental monitoring using satellite data.

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