Background and Objective: This study aims to identify and analyze the spatiotemporal patterns of mobility and deployment of extra-regional U.S. naval units in Southwest Asia through a data-driven and integrative framework based on statistical clustering analysis.
Methods: To achieve this objective, vessel position and timestamp data covering the period 2021–2024 were collected from open-source Automatic Identification System (AIS) feeds and Open-Source Intelligence (OSINT) reports, cleaned, and processed using Python and QGIS environments. The K-Means clustering algorithm was applied, with the Elbow and Silhouette methods employed to determine the optimal number of clusters. Model performance was assessed using the Davies–Bouldin Index and Silhouette Coefficient (1.12 and 0.78, respectively), confirming strong separation and high-quality cluster formation.
Findings: The analysis identified six primary clusters of naval activity concentrated in the Strait of Hormuz, the Gulf of Oman, the Bab el-Mandeb Strait, the Gulf of Aden, and the northern Indian Ocean. Temporal variations within these clusters demonstrated significant correlations with regional security events, multinational naval exercises, and geopolitical developments.
Conclusions: The results indicate that spatiotemporal clustering serves as an effective analytical tool for monitoring naval operations, anticipating potential threats, and enhancing foresight-based defense decision-making. This research contributes a practical, data-driven framework for examining maritime power dynamics within complex geopolitical systems and for advancing strategic foresight capabilities in defense and security planning.