Switzerland is a hazard-prone country at risk of floods, snow and ice avalanches, debris flows, landslides, and rockfalls. The Federal Institute for Forest, Snow and Landscape Research WSL estimated that more than 6% of the entire territory is exposed to landslides (mean 1972–2016). The vast literature existing on landslides normally neglects correlations among events in space and in time. However, recent studies indicate that further investigations in this direction are necessary. The present research analyzes the spatio-temporal pattern distribution of landslides in Switzerland with the aim of identifying clusters generated by the interaction between these two dimensions. Both global and local cluster indicators were applied to estimate the degree of clustering and to detect over-densities. Results revealed the presence of clusters at different scales, measured in terms of distances (in space) and frame periods (in time) where landslides are more likely to occur, which finally allowed to map and geovisualize the 3D structures of over-densities. Statistically significant local clusters were also detected and related with the surrounding meteorological condition to identify possible triggering events.