High-resolution topographic surveying is traditionally associated with high capital and logistical costs, so that data acquisition is often passed on to specialist third party organisations. The high costs of data collection are, for many applications in the earth sciences, exacerbated by the remoteness and inaccessibility of many field sites, rendering cheaper, more portable surveying platforms (i.e. terrestrial laser scanning or GPS) impractical. This paper outlines a revolutionary, low-cost, user-friendly photogrammetric technique for obtaining high-resolution datasets at a range of scales, termed ‘Structure-from-Motion’ (SfM). Traditional softcopy photogrammetric methods require the 3-D location and pose of the camera(s), or the 3-D location of ground control points to be known to facilitate scene triangulation and reconstruction. In contrast, the SfM method solves the camera pose and scene geometry simultaneously and automatically, using a highly redundant bundle adjustment based on matching features in multiple overlapping, offset images. A comprehensive introduction to the technique is presented, followed by an outline of the methods used to create high-resolution digital elevation models (DEMs) from extensive photosets obtained using a consumer-grade digital camera. As an initial appraisal of the technique, an SfM-derived DEM is compared directly with a similar model obtained using terrestrial laser scanning. This intercomparison reveals that decimetre-scale vertical accuracy can be achieved using SfM even for sites with complex topography and a range of land-covers. Example applications of SfM are presented for three contrasting landforms across a range of scales including; an exposed rocky coastal cliff; a breached moraine-dam complex; and a glacially-sculpted bedrock ridge. The SfM technique represents a major advancement in the field of photogrammetry for geoscience applications. Our results and experiences indicate SfM is an inexpensive, effective, and flexible approach to capturing complex topography.