Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs.