Spaceborne interferometric synthetic aperture radar has been proven to be able to monitor slow deforming landslides with mm-precision. Continental- and nationwide-scale Sentinel-1 PSI (persistent scatterer interferometry) datasets with millions of deformation time series are publicly available, e.g., via the European Ground Motion Service or the Ground Motion Service Germany. This creates the possibility for an increased routine use of PSI for landslide applications. However, the use of PSI datasets is often done by visual inspection. The huge amount of measurements makes visual inspection, subjective, time-consuming, and error prone due to outliers. This study demonstrates how spatial and temporal patterns of the PSI velocity and time series can be detected in a semi-automatic way to improve objective information extraction. Therefore, two landslides, namely, Trittenheim and Piesport landslides, in Germany are analyzed using Sentinel-1 PSI datasets from the Ground Motion Service Germany. The post-processing technique semi-automatically detects spatial clusters of deforming PS with a maximum LoS velocity of 18 and 7 mm/a in Trittenheim and Piesport landslides, respectively. Furthermore, a correlation and time-lag between the surface deformation and a potential triggering factor is found. Results show that an increase in climatic water balance accelerates landslide deformation at the investigated locations. Results are verified by a second independent Sentinel-1 PSI dataset from the Ground Motion Service Germany.