Toplica district represents an area in Southern Serbia with significant forms of geoheritage that have not been valorized yet. The aim of this pioneering study is to systematically analyze and evaluate all manifestations of the geodiversity in the Toplica district. Based on the geological importance, degree of attractiveness, and size, a total of six geosites were selected. The main goal of the study is to emphasize the insufficient utilization of huge geotourism potentials of the Toplica district and to determine the current geotourism development and geotourism potential of evaluated geosites. The geotourism suitability of each geosite is defined through comparative analysis. The Geosite Assessment Model (GAM) is used to assess the current state of the various elements of geodiversity in the study area. Positioning within the GAM matrix is defined by the values of the investigated parameters. Visualization of the distribution of the GAM indicators is an innovative approach for the interpretation of the obtained results. As a projection of the geotourism potential, the study presents the results of the traffic accessibility of geosites using the Geographic Information System (GIS)-based isochronous method. GIS and Digital Terrain Models are used in the visualization of the research area. The results of GAM apostrophize the current tourist value of Devil’s City, while the isochron analysis of GIS highlights the great geotourism potential of publicly little-known and touristically unaffirmed geosites. The results represent a basis that can support the affirmation of geotourism, the improvement of existing, and the development of new geotourism strategies in the Toplica district.

Most high-mountain regions worldwide are susceptible to snow avalanches during the winter or all year round. In this study, a Universal Snow Avalanche Modeling Index is developed, suitable for determining avalanche hazard in mountain regions. The first step in the research is the collection of data in the field and their processing in geographic information systems and remote sensing. In the period 2023–2024, avalanches were mapped in the field, and later, avalanches as points in geographic information systems (GIS) were overlapped with the dominant natural conditions in the study area. The second step involves determining the main criteria (snow cover, terrain slope, and land use) and evaluating the values to obtain the Snow Avalanche Formation Index (SAFI). Thresholds obtained through field research and the formation of avalanche inventory were used to develop the SAFI index. The index is applied with the aim of identifying locations susceptible to avalanche formation (source areas). The values used for the calculation include Normalized Difference Snow Index (NDSI > 0.6), terrain slope (20–60°) and land use (pastures, meadows). The third step presents the analysis of SAFI locations with meteorological conditions (winter precipitation and winter air temperature). The fourth step is the modeling of the propagation (simulation) of other parts of the snow avalanche in the Flow-R software 2.0. The results show that 282.9 km² of the study area (Šar Mountains, Serbia) is susceptible to snow avalanches, with the thickness of the potentially triggered layer being 50 cm. With a 5 m thick snowpack, 299.9 km² would be susceptible. The validation using the ROC-AUC method confirms a very high predictive power (0.94). The SAFI–Flow-R approach offers snow avalanche modeling for which no avalanche inventory is available, representing an advance for all mountain areas where historical data do not exist. The results of the study can be used for land use planning, zoning vulnerable areas, and adopting adequate environmental protection measures.

Abandoned mines can pose a major environmental hazard. At the beginning of the 21st century, significant steps were taken all around the world in order to protect these historically valuable complexes, and the mining heritage was recognized as a potential for the development of alternative tourism. This exploration covers mines in the Kopaonik Mountain area. Mining on this mountain began in ancient times. It has developed throughout history, and today only one mine is active. Three abandoned (Gvozdac, Suvo Rudište and Raičeva Gora) and one active mine (Belo Brdo-Zaplanina) are the subject of research. The basic aim of the research is twofold. The estimation of geo-tourist values was performed using the Geosite Assessment Model (GAM), and the ecological status assessment WAS performed according to the standard model based on negative and positive values. Based on the applied methods, it was concluded that mines (geosites) have a high level of natural characteristics, and that differences between geosites are evident in tourist values. The reason for this is insufficient tourist affirmation and the insufficient availability of tourist infrastructure. With the ecological status, positive values were observed on the geosites, which also differ from one (Raičeva Gora) to 15 points (Gvozdac). In the end, the results obtained are of great scientific importance, and their direct application is in the development of the Tourism Development Strategy in the Kopaonik area.

Railways that were once utilized by conventional speed trains but now lay technologically outdated and neglected are scarcely in use today, with many lying abandoned. These rail networks sprawl across vast areas, posing a substantial impediment to sustainable land use and management. Our research advocates for the adoption of tourist itinerary/route as a viable model for the transformation of abandoned railways into sustainable and functional systems. This innovative concept involves repurposing abandoned railways into tourist itineraries with the aim of utilizing them for tourism and commercial ventures. Recognizing a knowledge gap, particularly the absence of scientifically grounded models, on a selected case study (abandoned regional railway number 223 in the Toplica District, Serbia), we develop and present a model for the identification and Tourist Evaluation of Abandoned Railways (TEAR model). The defined model comprises a total of 27 sub-indicators categorized into four groups of indicators: natural tourist values (NV), anthropogenic tourist values (AV), tourist attractiveness of the railway (TA), and functional values (FV). The findings from the TEAR model suggest that the abandoned railway holds significant tourism value, with a rating of ≥0.7. Specifically, three sets of indicators—NV, AV, and TA—indicate a high level of tourist values (≥0.7), while FV falls within a moderate range of tourist values (0.4 ≤ V < 0.7). This endeavor not only supports sustainable local and regional development but also contributes to the enhancement of rural landscapes and the revitalization of rural areas. Importantly, this initiative aligns directly and indirectly with several Sustainable Development Goals (SDGs), thus fostering progress towards broader economic, societal, and environmental objectives.