Integrating Remote Sensing and Ground Observations to Discriminate Landslide Induction and Understand Trigger Interactions

Landslides are significant natural hazards frequently triggered by heavy rainfall and earthquakes, representing the most damaging secondary coseismic environmental effects. In geologically active regions like the Northern Apennines (Italy), high seismic hazard often couples with frequent large-scale slope failures. Global evidence suggests a complex interplay between triggers: earthquakes following intense rainfall tend to induce more landslides, while seismically impacted areas often show elevated landslide rates in subsequent years. Analyzing these tectonic-meteorological interactions is crucial for accurate hazard prediction.

The central goal of this research is to resolve the intricate interactions among tectonic, meteorological, and surface processes by evaluating the role of seismicity and rainfall (whether concurrent or not) in the evolution of slope failures. This presentation details the conceptual framework and preliminary implementation of a newly initiated project aimed at monitoring these dynamics in real-time. The investigation focuses on the fundamental mechanisms of landslide induction, considering pre- and post-seismic meteorological states to identify crucial triggering parameters.

The study utilizes a dedicated, multi-technique monitoring network at the Roncovetro landslide, a relatively young complex-earthflow, with a mean discharge rate of ∼ 0.16 × 10⁵ m³/yr, that serves as a natural laboratory for landslide characterization in the Apennines. To discriminate between induction mechanisms, we integrate:

• Remote Sensing Tools: Repetitive Unmanned Aerial System (UAS) surveys are employed to conduct high-resolution terrain analysis and quantify volumetric changes. Comparison of digital topography (including historical 1973 data vs. 2014–2025 datasets) allows for the assessment of long-term discharge rates and morphological evolution.
• Ground-Based Monitoring: An already existing local network of Global Navigation Satellite System (GNSS) stations and Ultra Wide Band (UWB) sensors provides high-frequency displacement data, enabling the correlation of movement with specific triggers. New GNSS stations will be installed in different sectors of the landslides in order to extend the real time analysis of the slope movements.
• Meteorological Data: Continuous hydro-meteorological parameters are gathered from a nearby weather station managed by the Regione Emilia Romagna, providing the high-resolution rainfall data necessary to establish triggering thresholds.
• Novel Geophysical Sensing: High-resolution seismic data will be acquired through Distributed Acoustic Sensing (DAS), leveraging fiber optic cables to create a dense linear array of seismic sensors at a 1-meter spatial scale.
• Field Analysis: Conventional geomorphological mapping and field-based geological surveys validate the remote sensing products and ground-truth the internal boundaries of the landslide body.

The availability of this integrated observational network will allow for the spatial and temporal discrimination of landslide sectors triggered by meteorological events versus those sensitive to seismic shaking. Future analysis of the Roncovetro site—an area already characterized by historical data and impacted by both significant earthquakes (e.g., the 1996 Mw 5.4 event) and recent extreme rainfall (2024–2025)—will try to highlight relationships between antecedent moisture conditions and seismic history to define slope stability. This integrated analysis is expected to provide fundamental insights into event timing, shaking intensity, and the ultimate magnitude of landslide movements. Ultimately, the project will offer a robust, multi-sensor framework for multi-hazard risk assessment in complex terrain.