## 6 Discussions
The identification of a risk situation is never a definitive operation that is carried out once and is effective forever, but rather a work in progress. An ideal update frequency is suggested in the previous sections. The data can be subdivided into those points that are static and those that are dynamic and need to be updated regularly. Examples of static datasets are related to geology, soil types, geomorphology, and morphography. The time frame for the updating of dynamic data may range from hours and days, for example, for meteorological data and its effect on slope movements, to months and years for land use and population data. **Improve knowledge in the mechanism of rock instability**. Additionally, a more in-depth study of landslide-triggering factors could help identify key elements necessary for calibrating the method, enhancing the framework's precision. This would also support the establishment of thresholds for various parameters used in the analysis. When defining these threshold parameters, the availability of historical events in the area can provide valuable data to further refine and calibrate the indices. Finally, it is essential to consider data timeliness to ensure that all information is temporally aligned for consistency across analyses. **Socio-Economic Impacts**. This study can also be the starting point for an economic estimate of the assets subject to natural hazards. Above, we are talking all about high-altitude ski facilities, and all the tourist and accommodation activities that surround this sector, but also about paths, natural areas that could be damaged, riverbanks to be rebuilt, and so on. **Integration with Machine Learning**: Combining the deterministic GIS framework with machine learning algorithms could uncover non-linear patterns in slope instability risks and improve hazard prediction. **Longitudinal Studies**: Monitoring changes in risk levels over time, especially in response to ongoing glacier retreat and climate change, could provide valuable insights for adaptive risk management. **Improving coordination**. Coordination between different municipalities (and at a higher level between different countries) in landslide disaster risk management is fundamental, including the drafting of emergency plans and the development of structural and non-structural measures. A low level of coordination between single municipality leads to a final representation of the surface process dynamics that is heterogeneous and incomplete and that henceforth generates unsatisfactory basin-scale planning. The approach proposed in this work overcomes most of such weaknesses, at least on a regional scale. **Expansion to Other Regions**: Testing the methodology in other mountainous regions worldwide would validate the proposed approach's robustness and highlight necessary adjustments for different geographical and climatic contexts. **Sensibility analysis**. Finally, it should also be recalled that estimates of risk are inevitably approximate and should not be considered as absolute values. This is best understood by allowing for the uncertainty in the input parameters, and in reporting the risk analysis outcomes. Furthermore, tolerable risk criteria are themselves not absolute boundaries. The level of risk acceptability is not universally defined: society shows a wide range of tolerance to risk, and the risk criteria are only a mathematical expression of the assessment of general societal opinion.