Detecting landslides is of paramount importance for preventing damage to people and historical sites, and for preserving the overall territory. Recently, satellite imagery—specifically Differential Interferometric Synthetic Aperture Radar (DInSAR)—has proven to be an effective solution for detecting and mapping landslides in various contexts. However, the applicability of satellite monitoring for landslide detection at large spatial scales, such as regional or national levels, is still under development. In this ongoing work, we present the EGMS-in-IFFI-dataset, which represents our effort to explore the potential of these techniques. Using a custom-developed Python code, we performed a spatial intersection of the data points provided by the European Ground Motion Service (EGMS) with the geometries of landslide areas stored in the Italian Landslide Inventory (Inventario dei Fenomeni Franosi in Italia - IFFI). We detail the resulting dataset and methodology, accompanied by an exploratory statistical analysis.