Landslides are complex phenomena controlled by natural and anthropogenic factors. In recent years, the need to understand their dynamics has driven the development of methodologies for improving risk monitoring and mitigation. In this context, landslide occurrence dating helps identify triggering causes and critical thresholds. This study introduces a fully automated and objective methodology, implemented on the Google Earth Engine platform, which allows access to and processing of large volumes of satellite data online, speeding up analyses and facilitating method sharing. The procedure exploits the complementarity between changes in vegetation cover detected through vegetation indices and changes in radar backscattering, intending to narrow the time window in which the landslide occurred. In 45 out of 46 cases analyzed, the time interval of landslide occurrence could be correctly identified, with a mean temporal window of approximately 8 days (range—3–12 days), confirming the robustness of the approach across different geomorphological settings and landslide types. The complete automation of the workflow is among the most innovative aspects of the methodology, as it allows the script to be directly and consistently applied to a wide range of recent and vegetated landslides with sizes larger than about 10 Sentinel-2 pixels without requiring additional manual procedures.
Barbera et al. (2025) studied this question.