An AIS–MRV Consistency-Enhanced Dynamic Network Framework for Shipping Traffic Resilience Assessment and Disruption Recovery Characterization

Coastal shipping systems experience complex functional degradation and recovery under port congestion, extreme weather, channel restrictions, and environmental constraints. To support sustainable maritime governance and port management, this paper proposes an AIS–MRV consistency-enhanced dynamic network assessment framework. The framework converts vessel trajectories into a dynamic maritime traffic network composed of ports, anchorages, fairways, and traffic corridors, and it constructs normal-state baselines by region, time window, and vessel type. It jointly measures system functionality, resilience loss, recovery time, network efficiency, anchorage congestion, route deviation, and an AIS-derived green operational penalty. It also compares AIS-derived green activity proxies with MRV annual CO2 reports to assess external consistency. The short-term real-AIS experiment identifies 70 traffic nodes and produces comparable functionality curves and Resilience–Green Index values for five representative port regions. The DGX full-year AIS baseline experiment processes 365 daily AIS files and generates 22.76 million vessel-hour records. Under network-parameter perturbations, the Spearman correlations of the Q* time series range from 0.900 to 1.000, and the Spearman correlation of the five-region RGI ranking remains 1.000. The Los Angeles/Long Beach event window shows a standardized functionality difference of −0.076 relative to spatial controls, with a bootstrap 95% confidence interval of [−0.090, −0.023]. The five regions show an index range of 0.3168–0.8391, and Puget Sound remains the top-ranked region in 86.27% of 10,000 random weight perturbations. The MRV consistency test indicates a moderate positive correlation between the AIS vessel-size proxy and annual CO2 emissions, while the size-weighted AIS activity proxy is also positively correlated with reported emissions. The framework provides a reproducible basis for identifying vulnerable shipping segments, assessing traffic recovery, and supporting port management, congestion governance, and green shipping decisions.