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Heterogeneous integrated dataset for Maritime Intelligence, surveillance, and reconnaissance
Ray, C.; Dréo, R.; Camossi, E.; Jousselme, A.-L.; Iphar, C. (2019). Heterogeneous integrated dataset for Maritime Intelligence, surveillance, and reconnaissance. Data in Brief 25: 104141. https://dx.doi.org/10.1016/j.dib.2019.104141
In: Data in Brief. Elsevier: Netherlands. e-ISSN 2352-3409, more
Peer reviewed article  

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Keyword
    Marine/Coastal

Authors  Top 
  • Ray, C.
  • Dréo, R.
  • Camossi, E.
  • Jousselme, A.-L.
  • Iphar, C.

Abstract
    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.

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