The accurate mapping of coalmine subsidence is necessary for the continued management of potential subsidence impacts. The use of airborne laser scan (ALS) data for subsidence mapping provides an alternative method to traditional ground-based approaches that affords increased accessibility and complete spatial coverage. This paper evaluates the suitability and potential of ALS data for subsidence mapping, primarily through the examination of two pre-mining surveys in a rugged, densely vegetated study site. Data quality, in terms of mean point spacing and coverage, is evaluated, along with the impact of interpolation methods, resolution, and terrain. It was assumed that minimal surface height changes occurred between the two pre-mining surfaces. Therefore any height changes between digital elevation models of the two ALS surveys were interpreted as errors associated with the use of ALS data for subsidence mapping. A mean absolute error of 0.23 m was observed, though this error may be exaggerated by the presence of a systematic 0.15 m offset between the two surveys. Very large (several metres) errors occur in areas of steep or dynamic terrain, such as along cliff lines and watercourses. Despite these errors, preliminary subsidence mapping, performed using a third, post-mining dataset, clearly demonstrates the potential benefits of ALS data for subsidence mapping, as well as some potential limitations and the need for further careful assessment and validation concerning data errors.