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Satellite Technology for Aquaculture and Fisheries Management

Satellite derived information, combined with correlation work is helping researchers to identify and link biological and environmental factors affecting fisheries and aquaculture. SAFIs research results will help in making more informed management decisions, in adjusting fishing efforts to conditions of fishing grounds and/or stocks, ensuring sustainable exploitation of living marine resources by utilising satellite data.
For aquaculture, SAFI researchers have created tools that will help to identify the best areas for fish and bivalve farming. These tools will also help monitor sites in near-real time, which will have a tremendous impact on product quality. This tool is applicable to fisheries management and can provide essential information for the implementation of fisheries policies.
Environmental characteristics measured from space using satellite data are advantageous due to wide spatial and temporal coverage, as well as researchers having free and open access to much of the data. Spatial and temporal models are being developed to produce indicators for environmental impacts on species traits.
SAFI models also intend to be able to forecast fish abundances, in order to estimate allowed catches for the following year. Case studies have been developed, based on a pelagic fishery off Portugal, and a second focusing on bivalves captured by a small scale fishery in Southern Portugal.
Once the models are developed, and have been comprehensively tested, SAFIs partners will apply them in other areas. SAFI’s correlation studies shall ensure that operators in these sectors who make use of the service can be confident that they are making decisions based on transparent and world-class scientific findings. SAFI partners have also developed a web-GIS where interested parties can access information for Europe and North Africa on topics such as sea surface temperature and ocean productivity.
Furthermore, the collaborative approach of the SAFI project has provided the IPMA team with a large database of calibrated historical environmental data for the fisheries areas under study, which allows us to merge the space and time dimensions for fisheries related studies. This will enable researchers to improve forecasts of fisheries resources using satellite data, opening further areas for future research.
Marta Ruffino (IPMA)