Terrestrial laser scanning is used to capture the geometry of three single folded bedding surfaces. The resulting light detection and ranging (LIDAR) point clouds are filtered and smoothed to enable meshing and calculation of principal curvatures. Fracture traces, picked from the LIDAR data, are used to calculate fracture densities. The rich data sets produced by this method provide statistically robust estimates of spatial variations in fracture density across the fold surface. The digital nature of the data also allows resampling to derive fracture parameters that are more traditionally measured manually from outcrops (e.g., one-dimensional line transects of fracture spacing). The fracture statistics derived from the LIDAR data are compared with the calculated principal and Gaussian curvatures of the surface to assess whether areas of extreme curvature correlate with high-fracture density. For the folds studied, all the fracture spacing distributions showed an exponential distribution, and no significant correlation between fracture density and surface curvature was observed. This questions the validity of using curvature as a proxy for high brittle strains and highlights the need for a complete understanding of fold and fracture mechanics that include considerations of other factors including lithology, strain rate, and confining pressure, not just finite strain. The three case studies also illustrate how terrestrial laser scanning can be used to gather detailed quantitative data sets on fracture and fold distributions from outcrop analogs.