Hierarchical-agglomerative clustering analysis of geomorphic features applied to tectonic investigation of terrestrial planets: An example from Claritas Fossae, Mars

A hierarchical-agglomerative clustering workflow is proposed to investigate regions on planetary surfaces. This algorithm comprises two primary steps: (i) calculating the dissimilarity between each object and (ii) grouping objects using a hierarchical clustering method. The efficiency of the workflow hinges on two critical parameters that require careful selection: the attributes for grouping objects and the number of clusters for interpretation. We applied this approach to tectonic lineaments in the Claritas Fossae (CF) region on Mars, a complex area significantly shaped by tectonic activity. Our analysis considered three attributes of these lineaments: (i) azimuthal direction, (ii) length, and (iii) centroid position. The optimal number of clusters was determined using the Silhouette index (S), which assesses the robustness of the clustering results. Our objectives were twofold: (i) to replicate the distribution of lineament sets obtained from classical geostatistical analysis of their azimuthal orientation and (ii) to refine the subdivision by varying combinations of the three attributes. Our results provide crucial insights into the geo-tectonic evolution of CF, supporting the hypothesis of a tectonic evolution characterised by a polyphase history. In addition, we demonstrate how the method is capable of effectively identified areas with varying intensities of brittle deformation.