# UAV-Based Evaluation of Rockfall Hazard in the Cultural Heritage Area of Kipinas Monastery, Greece
## 6 Conclusions
With the optimal failure model determined for each sub-region, a semi-automated procedure was performed in the 3D point cloud in order to monitor and quantify the magnitude (volume, mass) of both the already detached and fallen rock blocks and the prone ones for each sub-region. The final step before the implementation of the rating system was the conduction of a rockfall analysis based on trajectory simulations. This probabilistic analysis was performed via RocFall software v.8 (RocScience Inc., Toronto, ON, Canada) for four (4) different slope profiles, one for each sub-region, in order to determine the total kinetic energy of a potential rockfall event at the moment of impact, the velocity of the rock blocks and their \"bounce height\". With this methodology, all the essential data were obtained in order to provide values to all of the factors of the proposed rockfall hazard and risk rating system. In general, the proposed rating system defines four (4) major parameters categories which consist of a variety of different ranking values, in order to estimate the total risk level for each sub-region. Three (3) of these categories are related to the hazard level (geometry factors, geoengineering factors and triggering factors) and one (1) to the impact of a potential rockfall event. Every rating factor has a different weight, which is based on the significance of each individual contribution to either the hazard and/or risk level for every sub-region. Each examined factor can be evaluated between 10 and 100, as the conditions evolve from favorable to adverse, and then should multiplied by its respective predetermined weight. The total hazard score is calculated by summing the individual score of each factor, from the first three (A, B and C) major categories. At last, the total risk score is calculated by adding the fourth category (D) to the hazard score. Lastly, in a subsequent step, in order to estimate the outcome of this rockfall hazard and risk assessment and also gain important feedback for the proposed rating system, research should continue to be performed in the cultural heritage area of Kipinas Monastery. In particular, regular monitoring of the slope, ideally per six months or annually, with a UAV is suggested in order to compare the obtained data. Through this multi-temporal change detection procedure between the different datasets, topographical changes between different epochs could be monitored and characterized for robust modeling of rockfall dynamics, as suggested by [70; 106; 107]. With these results, mitigation measures could be quantified and suggested for the unique needs of each sub-region. Additionally, via these outcomes, an immediate evaluation and calibration, if needed, could be performed of the proposed rating system in order be as precise and accurate as possible. This constant evaluation is necessary because the main target of this proposed rockfall hazard and risk rating system is to be considered as the transitional step between qualitative and quantitative assessments. Author Contributions:Conceptualization, I.K., V.M. and G.P. ; methodology, I.K. ; software, I.K. ; validation, I.K., V.M. and G.P. ; formal analysis, I.K. ; investigation, I.K., V.M. and G.P. ; data curation, I.K., V.M. and G.P. ; writing--original draft preparation, I.K. ; writing--review and editing, I.K., V.M. and G.P. ; visualization, I.K. ; supervision, I.K., V.M. and G.P. ; project administration, I.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest.