This master’s thesis presents an analysis of the ownership structure of legal entities and the value of building parts in landslide-prone areas in Slovenia using geoinformation tools and statistical analyses. The purpose of the work was to classify legal entities into the appropriate owner types and to assess the exposure of their property with regard to the probability of landslide occurrence. The analyses were based on publicly available data from the Valuation Register of Slovenia, the Business Register of Slovenia, the Register of Budget Users and publicly available warning maps of the probability of landslides and mountain landslides at a scale of 1:25,000, which apply only to the areas of individual municipalities and not to the entire territory of Slovenia. The analysis of the ownership of legal entities was carried out in the Oracle environment using the structured query language SQL, where owners were classified into appropriate owner types in accordance with the criteria of the methodology. The spatial analysis of the exposure of parts of buildings owned by legal entities with regard to the probability of landslide occurrence was carried out in the QGIS environment. The results provided insight into the ownership structure of legal entities that own parts of buildings in landslide-prone areas, into the value of building parts and the exposure of assets to the probability of landslides. It was found that the share and value of building parts located in areas with a medium to very high probability of landslide occurrence are not negligible and indicate high potential damage in the event of natural disasters. The analysis showed differences between owner types, valuation models and the exposure of municipalities to the probability of landslides. Based on the results, it was found that the combination of spatial data on the probability of landslides, building parts and its value and actual use represents an effective tool for assessing the exposure of assets to natural hazards. Suggestions for further analyses are also given that will contribute to more efficient spatial management and risk reduction through preventive measures and preparedness.
|