Abstract. Analysing the spatial arrangement, connectivity, and evolutionary history of complex fault networks is essential for quantifying strain distribution in active deformational zones, and evaluating associated geohazard and resource potentials. The structure and evolution of fault networks are commonly investigated using a range of methods, including the analysis of topographic data derived from satellite imagery, numerical modelling, as well as physical experiments. The high density and intrinsic complexity of fault systems in many study areas or models pose significant challenges for automated analysis, often necessitating time-intensive manual interpretation. Here, we present Fatbox, the Fault Analysis Toolbox, an open-source Python library that integrates semi-automated fault extraction with automated geometric and kinematic analysis of fault networks. The toolbox capabilities are demonstrated through three case studies on normal fault systems, each drawing on a different data type: (1) fault extraction and geometric characterization using GLO-30 topographic data in the Magadi-Natron basin in East Africa; (2) spatio-temporal tracking of fault development in vertical cross-sections of a forward numerical rift model; and (3) surface fault mapping and geometric evolution of a physical rifting experiment. Fatbox represents fault networks as topological graphs, comprising nodes (i.e., points) and edges (i.e., lines) connecting the nodes. In time-dependent models, the toolbox enables temporal tracking of faults, providing detailed insights into their geometric evolution and facilitating high-resolution measurements of fault kinematics. Fatbox offers a versatile and scalable framework that enhances the efficiency, reproducibility, and precision of fault system analysis – opening new avenues for tectonic research.
Gayrin et al. (Tue,) studied this question.