Debris-covered glaciers play an important role in the high-altitude water cycle in the Himalaya, yet their dynamics are poorly understood, partly because of the difficult fieldwork conditions. In this study we therefore deploy an unmanned aerial vehicle (UAV) three times (May 2013, October 2013 and May 2014) over the debris-covered Lirung Glacier in Nepal. The acquired data are processed into orthomosaics and elevation models by a Structure from Motion workflow, and seasonal surface velocity is derived using frequency cross-correlation. In order to obtain optimal surface velocity products, the effects of different input data and correlator configurations are evaluated, which reveals that the orthomosaic as input paired with moderate correlator settings provides the best results. The glacier has considerable spatial and seasonal differences in surface velocity, with maximum summer and winter velocities 6 and 2.5 m a–1, respectively, in the upper part of the tongue, while the lower part is nearly stagnant. It is hypothesized that the higher velocities during summer are caused by basal sliding due to increased lubrication of the bed. We conclude that UAVs have great potential to quantify seasonal and annual variations in flow and can help to further our understanding of debris-covered glaciers.