Port calls and vessel trajectory dataset in the Caribbean with accurate port quays survey.

With the growth in maritime traffic comes an increased need for precise modelling, analysis, and visualisation to enhance the monitoring capabilities of maritime authorities. To address this need, a range of sensing technologies have been developed to track vessel movements worldwide. Among these, the Automatic Identification System (AIS) is particularly significant, offering high-frequency transmission of both location and identification data. This makes AIS an invaluable tool in the intricate process of modelling maritime traffic that we use in this study. Our study presents a comprehensive dataset for the Caribbean in 2019, including port calls, quay geometries, vessel trajectories, daily locations, a seven-class vessel classification, port statistics, and United Nations reference data for comparison. Beneficial for geomatics, geography, and economics, the dataset provides a versatile tool for visualising data, assessing maritime impact on coastal areas, and enhancing maritime trade analysis. The methodology extracts 1.5 million port calls from 642 million AIS messages, offering detailed data tables and reusable processes. Its granularity down to the single quay allows for flexible data analysis, facilitating in-depth understanding of port and inter-port maritime activities.

Maritime route and vessel tracklet dataset for vessel-to-route association.

With an ever-increasing number of vessels at sea, the modelling, analysis and visualisation of maritime traffic are of paramount importance to support the monitoring tasks of maritime stakeholders. Sensors have been developed in this respect to track vessels and capture the maritime traffic at the global scale. The Automatic Identification System (AIS) is transmitting maritime positional and nominative information at highest frequency rate, making it a valuable source for maritime traffic modelling. From an original AIS dataset covering the area of Brest, France, we extracted a set of 17 maritime routes, connecting ports in this area. Two different representations for the routes are provided: (1) clusters of AIS contacts, and (2) route prototypes, representing the nominal trajectory of the vessels following the route. Additionally, a set of tracklets (built by five consecutive AIS contacts from the same vessel trajectory) has been extracted from the set of routes and the original dataset, and labelled either with the route name to which they belong or as off-route tracklets. This dataset provides thus some ground truth on the routes followed by vessels and is aimed at testing and validating vessel-to-route or track-to-route association algorithms.

Heterogeneous integrated dataset for Maritime Intelligence, surveillance, and reconnaissance.

Facing an ever-increasing amount of traffic at sea, many research centres, international organisations, and industrials have favoured and developed sensors together with detection techniques for the monitoring, analysis, and visualisation of sea movements. The Automatic Identification System (AIS) is one of the electronic systems that enable ships to broadcast their position and nominative information via radio communication. In addition to these systems, the understanding of maritime activities and their impact on the environment also requires contextual maritime data capturing additional features to ships' kinematic from complementary data sources (environmental, contextual, geographical, …). The dataset described in this paper contains ship information collected through the AIS, prepared together with spatially and temporally correlated data characterising the vessels, the area where they navigate and the situation at sea. The dataset contains four categories of data: navigation data, vessel-oriented data, geographic data, and environmental data. It covers a time span of six months, from October 1st, 2015 to March 31st, 2016 and provides ship positions over the Celtic sea, the North Atlantic Ocean, the English Channel, and the Bay of Biscay (France). The dataset is proposed for an easy integration with relational databases. This relies on the widespread and open source relational database management system PostgreSQL, with the adjunction of the geospatial extension PostGIS for the treatment of all spatial features of the dataset.