FOSS4G IT & OSMit 2026

Rockfalls are rapid, high-energy slope processes that can severely affect buildings, infrastructure, and human safety, particularly where steep rocky slopes interact with urbanized environments. Their assessment is especially challenging at medium scale, where large territories must be analyzed through simplified but reliable procedures, and where the recurrence of different rockfall scenarios should be explicitly considered. In this context, preliminary risk analyses are essential to support land-use planning, mitigation prioritization, and the identification of sectors requiring more detailed investigations.
This study presents a GIS-based procedure for preliminary time-dependent rockfall risk assessment, developed to support spatially distributed risk screening through the explicit inclusion of temporal probability. The workflow is organized in two main phases within an open-source QGIS environment. The first phase concerns hazard analysis and is performed using the QPROTO Plugin (Castelli et al., 2021), adopted to estimate potential invasion areas and characterize rockfall intensity for different block-volume scenarios through a simplified physical-based estimation of the kinetic energy of the block.
The second phase concerns risk assessment and is carried out through the QRADE plugin, which applies the IMIRILAND methodology (Bonnard et al., 2004) to integrate hazard outputs with the vulnerability and value of exposed elements. Starting from a hazard dataset representing block kinetic energy, QRADE assesses the vulnerability of exposed elements using predefined but fully customizable tables derived from the literature (Torsello et al., 2022). Exposed elements can be provided by the user or downloaded automatically directly from OpenStreetMap (OSM). By leveraging OSM’s taxonomy and tags, QRADE assigns a specific vulnerability rating to each identified element (e.g., buildings, roads, or infrastructure). Based on classifications of the elements’ value, proposed by the plugin but also fully customizable, a risk index is then calculated for each element.
When assessing the vulnerability and value of the elements, physical aspects (damage to structures or buildings) and social aspects (harm to people) are considered separately. The final result then consists of three risk maps: Physical Risk, Social Risk, and Total Risk, which is equal to the sum of the first two.
To account for the time-dependent component of risk, different rockfall volume scenarios can be associated with probabilities of occurrence over selected reference periods, through a probabilistic formulation based on historical event recurrence. This allows the procedure to move beyond a purely spatial assessment by considering not only the expected effects of the phenomenon, but also its likelihood over time. In this way, the framework provides a more informative basis for preliminary decision-making in comparison with time-independent approaches.
The methodology is applied to the Palermo area in southern Italy, considered a representative case study given the interaction between steep rocky slopes and exposed urban elements, as well as the need to develop and test practical tools for evaluating the effects of climate change in the Mediterranean context. The proposed approach produces hazard and risk maps for multiple scenarios and offers a rapid, transparent, and scalable framework for the preliminary evaluation of rockfall-prone areas. Although intended as a screening-level methodology, it provides useful support for identifying critical sectors, guiding subsequent site-specific analyses, and informing mitigation and risk-management strategies. More broadly, the procedure contributes to the development of operational GIS-based tools for preliminary time-dependent geohazard risk assessment in data-limited contexts.

References
Castelli M., Torsello G., Vallero G., 2021. Preliminary Modeling of Rockfall Runout: Definition of the Input Parameters for the QGIS Plugin QPROTO. In: GEOSCIENCES, vol. 11. https://doi.org/10.3390/geosciences11020088
Torsello G., Vallero G., Milan L., Barbero, M., Castelli M., 2022. A Quick QGIS-Based Procedure to Preliminarily Define Time-Independent Rockfall Risk: The Case Study of Sorba Valley, Italy. In: GEOSCIENCES, vol. 12. https://doi.org/10.3390/geosciences12080305
Bonnard Ch., Forlati F., Scavia C. (eds), 2004. Identification and mitigation of large landslide risks in Europe: advances in risk assessment. A.A. Balkema, ISBN 90 5809 598 3