Here is the link to the second phase of this Research Topic: https://www.frontiersin.org/research-topics/69624/big-data-and-ai-for-sustainable-maritime-operatio%E2%80%A6 ('Big Data and AI for Sustainable Maritime Operations')

Maritime activities continue to expand in scale and intensity as global vessel navigation, port logistics, offshore development, and marine resource use grow in complexity. These activities now play a defining role in shaping ocean and coastal systems, influencing ecological conditions, altering patterns of maritime risk and safety, and affecting the environmental and socio-economic resilience of coastal regions. In this evolving context, Big Data and artificial intelligence (AI) are becoming essential instruments for understanding the impacts of maritime operations, identifying emerging vulnerabilities, and guiding the transition toward sustainable, low-impact, and climate-resilient maritime systems.

As digital technologies advance, the maritime domain is experiencing a profound shift in how environmental impacts, operational risks, and ocean-system dynamics are observed and managed. Big Data analytics, machine learning, large language models, and emerging multimodal AI techniques now offer unprecedented capacity to integrate diverse data sources, reveal hidden patterns underlying maritime activities, and support real-time decision-making across both operational and ecological dimensions. These capabilities open new pathways for reducing accident risks, strengthening system resilience, enhancing environmental stewardship, and enabling evidence-based governance at the intersection of maritime operations and ocean sustainability. This Special Issue seeks contributions that demonstrate how big data and AI can drive enduring improvements in maritime safety, decarbonization, ecological protection, and the sustainable development of ocean and coastal systems.

Topics of interest include, but are not limited to:
 Sustainable and climate-resilient maritime infrastructure, port systems, and coastal logistics
 AI-enabled monitoring and assessment of maritime impacts on ocean climate, biodiversity, and sensitive marine habitats
 Big Data analytics for full-chain decarbonization of shipping, including emission reduction, energy efficiency, and alternative fuels
 Digital twins and predictive modelling frameworks supporting climate-adaptive planning for ports, coastal regions, and maritime corridors
 Data-driven methods that advance blue economy strategies and circular resource systems in maritime and coastal contexts
 AI and machine-learning approaches for sustainable fisheries management, detection of Illegal, Unreported and Unregulated (IUU) fishing, and broader maritime conservation initiatives
 Real-time environmental intelligence and dynamic condition monitoring to support safe, low-impact, and climate-aware vessel routing and maritime operations
 Integrated decision-support systems that connect maritime policy, ecological priorities, stakeholder needs, and digital innovation
 Socio-ecological modelling to enhance maritime safety, accident prevention, community resilience, and long-term coastal planning
 Applications of large language models (LLMs), foundation models, and multimodal AI for maritime analytics, risk assessment, environmental interpretation, and operational decision-making

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Big Data and Artificial Intelligence for Sustainable and Nature-Positive Ocean and Coastal Systems