Abstract
Tidal stream environments are areas of marine coastline that produce predictable current velocities exceeding 1 m/s. This leads to the production of ephemeral turbulent features, created due to site-specific topography and bathymetry, such as kolk-boils that vary across fine spatio-temporal scales (metres and seconds). Tidal stream environments are used by seabirds for foraging purposes but are also targeted for the installation of tidal energy devices. As there is likely an overlap in habitat occupancy between seabirds and devices, regulatory bodies require empirical evidence to quantify the environmental effects of developments.However, tidal stream environments are dynamic and it is challenging to collect data within them at fine spatio-temporal scales. Unmanned aerial vehicles (UAVs) offer a cost-effective solution to collect data at resolutions appropriate for capturing fine-scale seabird usage patterns. With the concurrent advances of image processing techniques, particularly through automation, there is the opportunity to increase both the frequency and accuracy of these data.
This work manually processed UAV imagery from the Inner Sound of the Pentland Firth in Scotland, to characterise kolk-boils in relation to key physical variables. Seabird habitat usage patterns were also examined in relation to kolk-boil and hydrodynamic variables. Finally, a feasibility study was undertaken to examine the potential of deep learning methods to automatically detect kolk-boils within UAV imagery.
This work provided novel outputs regarding the characterisation of kolk-boils, and highlighted trends based on current velocity and tidal phase that allowed them to be mapped and predicted across a site. Results also showed novel habitat usage patterns by diving seabirds (auks) including associations with individual kolk-boils and auk body orientation relative to the flow at the surface. Finally, this work demonstrated methodology for UAV usage within a tidal stream environment and provided a tool for monitoring with a clear development path for future optimisation.
| Date of Award | 18 May 2023 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Sponsors | Interreg VA - Cross Border |
| Supervisor | Benjamin Williamson (Supervisor) & Jason McIlvenny (Supervisor) |