Automated detection and tracking of marine mammals in the vicinity of tidal turbines using multibeam sonar

Funding: The monitoring platform was developed with funds from the Natural Environment Research Council (Grant Nos. NE/R015007/1 and NE/R014639/1). Software development and data analysis was funded by the Scottish Government as part of the Marine Mammal Scientific Support Program (Grant No. MMSS/002/15). Umbilical cables to the turbine infrastructure were funded and developed by SIMEC Atlantis.Understanding how marine animals behave around tidal turbines is essential if we are to quantify how individuals and populations may be affected by the installation of these devices in the coming decades. Our particular interest is in collision risk, and how this may be affected by the fine-scale behaviour of seals and small cetacean species around devices. We report on a study in which multibeam sonar data were collected close to an operational tidal turbine in Scotland continuously over a twelve-month period. The sonars provide high-resolution (a few cm) data over a 120° angle out to a range of 55 m at a rate of 10 frames per second. We describe a system which uses automatic computer algorithms to detect potential targets of interest, verified by human analysts using a sophisticated computer user interface to confirm detections and assign target species. To date, we have identified 359 tracks of marine mammals in the data, as well as several thousand tracks from fish and diving birds. These are currently being parameterised to study how these species react to the moving turbine rotors, and the data are now being used to explore the development of improved automated detection and classification algorithms.Publisher PDFPeer reviewe

Automated detection and tracking of marine mammals in the vicinity of tidal turbines using multibeam sonar

Understanding how marine animals behave around tidal turbines is essential if we are to quantify how individuals and populations may be affected by the installation of these devices in the coming decades. Our particular interest is in collision risk, and how this may be affected by the fine-scale behaviour of seals and small cetacean species around devices. We report on a study in which multibeam sonar data were collected close to an operational tidal turbine in Scotland continuously over a twelve-month period. The sonars provide high-resolution (a few cm) data over a 120° angle out to a range of 55 m at a rate of 10 frames per second. We describe a system which uses automatic computer algorithms to detect potential targets of interest, verified by human analysts using a sophisticated computer user interface to confirm detections and assign target species. To date, we have identified 359 tracks of marine mammals in the data, as well as several thousand tracks from fish and diving birds. These are currently being parameterised to study how these species react to the moving turbine rotors, and the data are now being used to explore the development of improved automated detection and classification algorithms