As we approach the first array deployments of tidal stream turbines, the risk of collisions between moving components of devices and deep-diving seabirds need assessing at population levels. Part of assessing risks is quantifying the extent to which the foraging distributions of deep-diving seabirds overlap with the potential locations of devices in the large tidal pass habitats favoured for array installations (spatial overlap). Shore-based surveys using single vantage points and extensive grid systems to record the locations of foraging birds are often used in large tidal passes. Here, an application of these methods in the Fall of Warness (FOW), Orkney, UK are used to evaluate their effectiveness for quantifying and statistically analysing spatial overlap in large tidal passes. Whilst it was possible to quantify and statistically analyse spatial overlap using the methods evaluated here, viable statistical analysis required data sacrifices through the use of presence rather than abundance data. Moreover, comparisons between simultaneous shore-based and boat-based surveys, which are assumed to represent an accurate method, showed that sightings in the former were biased towards non-turbine microhabitats. This shore-based survey bias reflected low detection rates of foraging birds in fast unidirectional currents away from coastlines. Therefore, the methods evaluated here are unsuitable for quantifying and statistically analysing spatial overlap in large tidal passes. It is suggested that future shore-based surveys should overcome aforementioned issues by using several vantage points spread throughout large tidal passes, and comparing species use of neighbouring turbine and non-turbine microhabitats at reasonable distances to the vantage points (<2 km) during favourable sea states (Beaufort Scale < 3). It is hoped that these recommendations lead to the development of standardised shore-based survey methods, providing comparable measurements of spatial overlap across tidal passes earmarked for array deployments: a key step towards estimations of collision risks at population levels.