A Spatial Framework for Extracting Suez Canal Transit Information from AIS

The Suez Canal is one of the world's most important maritime routes, as shown by the almost 19,000 transits made every year. Despite its importance to seaborne trade, few statistics about the operation are available. This paper outlines a method to generate transit information from the matching of Automatic Identification System (AIS) ship tracking data and the modeled spatial environment of the Suez Canal. Additionally, important features such as the waiting time at anchor and the access routes to the Canal are extracted from adjustments to Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The algorithm is designed to be deployed in a distributed setting for the handling of big data sets.