The spatiotemporal heterogeneity of global shipping patterns and chokepoints: evidence from geopolitical events in two regions
Abstract
Geopolitical disruptions increasingly affect maritime transportation networks, yet their spatially heterogeneous impacts on global shipping activity remain insufficiently understood. This study develops a two-scale analytical framework to investigate the spatiotemporal evolution of global shipping activity and examine regional responses associated with geopolitical disruptions in the Red Sea and the Arctic Ocean. Historical Automatic Identification System (AIS) data were processed to reconstruct vessel trajectories, aggregated into spatial grids, and analyzed using a space-time cube model and emerging hot spot analysis. At the global scale, the framework identifies persistent, intensifying, diminishing, and emerging patterns of shipping activity, revealing substantial spatial heterogeneity across major shipping corridors and maritime chokepoints. At the regional scale, the comparison between the Red Sea and the Northern Sea Route cases demonstrates differentiated response patterns under distinct geopolitical contexts. In the Red Sea region, AIS-derived observations show a rapid redistribution of vessel activity between the Red Sea-Suez Canal corridor and the Cape of Good Hope route. In contrast, Arctic shipping activity exhibited stronger temporal fluctuations and spatial heterogeneity, reflecting the combined influence of geopolitical conditions, environmental variability, infrastructure development, and resource-related activities. The findings indicate that geopolitical disruptions are associated with heterogeneous adjustments in maritime networks, with different regions exhibiting distinct patterns of route redistribution, activity concentration, and temporal persistence. The proposed framework provides a data-driven approach for monitoring changes in maritime activity, identifying vulnerable corridors, and improving understanding of shipping-network resilience under geopolitical uncertainty.