Enhancing Maritime Domain Awareness on Inland Waterways: A You Only Look Once-Based Fusion of Satellite and Automatic Identification System for Vessel Characterization

Maritime domain awareness (MDA) in inland waterways is constrained by vulnerabilities in cooperative monitoring systems. This study presents a data fusion framework that integrates high-resolution satellite imagery with vessel trajectory data from the automatic identification system (AIS) to enhance detection, characterization, and tracking of maritime activity. The proposed approach leverages noncooperative satellite sensing to complement AIS data, enabling the identification of dark vessels, validation of cooperative traffic, and support for advanced MDA capabilities. A You Only Look Once (YOLO) v11-based object detection model is developed to detect and characterize vessels and barges by type, cover status, operational state, barge count, and direction of movement. The model is trained on a manually annotated dataset comprising 4,550 instances extracted from 5,973 mi 2 of Lower Mississippi River imagery. Evaluation on a held-out test set demonstrates strong performance across multiple tasks, with vessel classification achieving an F1-score of 95.8%, barge cover detection attaining an F1-score of 91.6%, and operational status classification reaching an F1-score of 99.4%. Direction-of-movement classification attains an accuracy of 98.1%, while barge-count estimation yields a mean absolute error of 2.4 barges. Spatial transferability assessment across a geographically distinct river system indicates minimal performance degradation, with accuracy levels remaining as high as 98%. These results demonstrate the effectiveness of integrating satellite imagery with AIS data for inland waterway monitoring. The framework supports near-real-time fleet inventory generation, anomaly detection, and improved situational awareness. Future work will focus on expanding dataset diversity, incorporating temporal modeling, and exploring multimodal learning to further enhance scalability and operational deployment.