Cost benefit analysis of survey methods for assessing intertidal sediment disturbance: A bait collection case study

Abstract

Coastal management requires cost-effective, yet accurate, assessments of habitat condition, especially in areas protected by statutory conservation measures. Unmanned Aerial Vehicles (UAVs) provide alternatives to manned aircraft and walk-over (WO) surveys. To support coastal managers with method selection, we compare the costs and benefits of the three techniques using the extent of bait collection (sediment scarring from manual digging) on intertidal mudflats from three UK sites. UAV and WO surveys were conducted in parallel and aerial photography was downloaded from the Channel Coastal Observatory (CCO). Digging was digitised from estimations on foot (WO) or by manually labelling imagery with confidence assigned (UAV/CCO). Method efficacy is compared with respect to spatial coverage, control over survey time/location, spatial resolution, positioning accuracy, and area of digging detected. Personnel hours and up-front costs (e.g. training/equipment), costs for personnel time standardised by shore area, personnel risk, and environmental impact are also compared. Regarding efficacy, CCO imagery had extensive shore coverage compared to UAV and WO, however, assessments are restricted to times/locations with available imagery. Each method's resolution was sufficient to detect digging. WO achieved the highest resolution (on foot), but the lowest positioning accuracy, in contrast to accurate feature delineation on aerial imagery. An additive two-way ANOVA revealed a significantly higher percent area of ‘dug’ sediment (all confidence levels) recorded by UAV than WO. CCO was the most cost-effective with no fieldwork/equipment costs. UAV had the highest up-front costs, but WO was more costly for personnel hours/km2 for survey time and digitisation. For all methods, digitisation was the most time-consuming aspect. Compared to WO, UAV achieved rapid shore surveys and the CCO and UAV methods minimise personnel risks. UAV and WO both cause wildlife disturbance, with trampling an additional WO impact. With each method suited to sediment disturbance assessment, selection will depend on resources and objectives and will be aided by this holistic cost-benefit analysis. Cost-effectiveness will improve with evolving regulations that facilitate UAV use and technological developments (e.g. machine learning for disturbance detection) that could significantly expedite imagery analysis and enable broadscale assessments from CCO or satellite imagery.