Offshore wind farm surveys of marine megafauna: standardisation of tools and methods for monitoring at farm scales

Duration: 36 months (2020-2023)


Digital methods for monitoring marine megafauna from the air have undergone significant technical developments in recent years. Surveys based on these techniques will soon be used for the environmental monitoring of various French offshore wind projects. Given the economic stakes involved, it is necessary to demonstrate the technical relevance of these methods while guaranteeing commensurability with existing data from manned aerial surveys. Additionally, environmental platforms, such as multisensory buoys, are being increasingly deployed to monitor marine megafauna. However, data fusion combining multiple sources data is not yet developed and represents an important milestone for automated future surveys.


  • To provide an operational roadmap for conducting a robust inter-calibration of marine megafauna aerial surveys at ORE farm scale by using historical and novel technologies.
  • To improve the efficiency of multiple sensors in detecting, identifying and characterising marine megafauna by using an AI tool.

Scientific and technical contents

  • Inter-calibration methodology between digital and human-based aerial surveys
  • Development of AI solutions to enhance identification and estimation of targets (birds, marine mammals) coupling multimodal data (radar, acoustic)
  • Technical recommendations for marine megafauna monitoring in ORE project to ensure inter-operability of datasets
  • Cost-effectiveness analysis of sampling strategies using different acquisition methods


Project sheet (PDF)

Partners and funding

This project is led by IRISA (Université de Bretagne Sud) and France Energies Marines.

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The total budget project is €1,447K.
This project receives funding from France Energies Marines and its members and partners, as well as French State funding managed by the National Research Agency under the France 2030 investment plan.

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Photo credit: L’Avion Jaune

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