First Insights into Vessel Traffic Monitoring in the Gulf of Catania, Western Ionian Sea, Using a Fibre-Optic Cable and Distributed Acoustic Sensing

This study presents a preliminary analysis of vessel noise detection using Distributed Acoustic Sensing (DAS) along a deep-sea fibre-optic cable in the Gulf of Catania, Western Ionian Sea. We analyse ship-generated acoustic signatures recorded by a long-range DAS system prototype, deployed within the VONGOLA (Visual and nOise-eNhanced AI Analysis for Marine Biodiversity MonitorinG, Observation and LeArning) project. These data are examined in conjunction with Automatic Identification System (AIS) ship tracks to characterise the acoustic signatures of passing vessels and evaluate the system's detection range across different cable geometries and depths. Results indicate that DAS sensitivity is strongly influenced by cable geometry, with detection ranges exceeding 20 km in straight sections but significantly shorter in deeper, irregularly aligned cable sections. These findings lay the foundation for developing automated detection algorithms. Additionally, this work contributes to ongoing biodiversity assessments within VONGOLA, primarily focused on fin whales, by improving our understanding of how anthropogenic noise is captured in DAS data. Future efforts will refine detection capabilities and integrate DAS with hydrophone data for enhanced marine soundscape monitoring.