Quantitative analysis tools have become increasingly common in structural geology. Imaging techniques such as computed tomography are used to build highly accurate, three-dimensional models of geological structures. Structural measurements are facilitated and often accelerated owing to photogrammetric methods of reconstructing the studied outcrops. Geological structures can then be classified using statistical methods. These new methods allow for the integration of observations and quantification on scales which were inaccessible before. Experimental, analytical, and numerical techniques are used to develop quantitative mechanical models of rock deformation processes, and with the advent of modern computing power, high-resolution models and systematic simulations are nowadays feasible. Remote sensing techniques, including airborne or terrestrial photogrammetry and lidar, make it possible to realize exquisitely detailed three-dimensional (3D) topographic datasets from outcrop to regional scales. These technologies allow detailed, quantitative geological analysis in inaccessible, even extra-terrestrial, terrain. The data-reduction process that transforms these rich datasets into geologically meaningful descriptions of the structure and composition of outcropping rocks is, however, a significant challenge. Recent developments in this area are paving the way for novel geological analysis, incorporating data analysis techniques such as 3D interpolation, machine-learning, (semi-)automatic techniques, and immersive visualization.

We invite contributions discussing advances and challenges in quantifying geological structures at all scales.