Thanks to tracking data of fishing vessels, it is possible to derive information about the fishing habits of coastal communities and to know, for example, which are the areas where they fish more frequently. This information is crucial to tailor policy and management strategies to boost blue growth, the EU strategy for a more profitable and sustainable exploitation of marine and maritime resources.
The new tool "Mapping fishing activities" (MFA) uses for the first time tracking data from the Automatic Identification System (AIS) – used worldwide to identify and locate vessels thorough data exchange with other nearby ships, AIS base stations, and satellites – to analyse the relations between fishing communities and fishing areas at high level of geographical detail at EU-wide scale.
The data used in this tool consists of around 150 million positions from EU fishing vessels above 15 m in length in the period between September 2014 and September 2015. The MFA includes several layers of geographical information and a high-resolution map of fishing intensity covering all EU waters. Information on the position of vessels in relation to areas of high fishing intensity and in the surrounding of ports is aggregated into a dependency index which represents the gravitation of coastal communities towards specific fishing grounds and other ports.
Until recently such analyses have been based on highly aggregated figures from administrative sources such as the logbooks and the Vessel Monitoring System (VMS), which have been introduced to control fishing. The MFA relies on open source data from the AIS which, while not suitable for a systematic control of potentially illegal fishing, is more accessible and offers new possibilities for research.
Policy makers, scientists, experts can use this detailed data on fishing activity for fisheries management and fisheries research both from an environmental and a socio-economic perspective. By knowing where fishing activities are more intensive, it is possible for example to assess the impacts from trawling on the seabed floor and derive the indicators on fishing pressure envisaged by the Maritime Strategy Framework Directive.
Moreover, this information allows understanding which coastal communities would be most affected in economic and employment terms if restrictive measures on fishing activities are set in a specific area.
To preserve confidentiality all the information is aggregated from individual vessels to the level of ports and figures of dependency are presented only for ports with more than five vessels in the AIS data set.
The tool and method developed by the JRC shows the potential of AIS data to support fisheries management. The MFA spatial layers can be easily incorporated in other platforms that regularly disseminate marine data.
