شناسایی پهنه‌های مستعد احداث پیست اسکی با استفاده از سیستم اطلاعات جغرافیایی (مطالعه موردی: کوه آبیدر در شهرستان سنندج)

Paying attention to various factors, including sustainable development, distance and proximity to factors, is very important in choosing suitable locations. This study evaluates the appropriate location of a ski resort in the Abidar Tourism Mountain in Sanandaj by combining remote sensing and geographic information system. For this purpose, geological maps, Sentinel 2 satellite images, and ALOS-Pulsar DEM were prepared, and twelve environmental factors including altitude, slope, aspect, geology, faults, land cover, distance from the river, river density, distance from roads, road density, safe haven, and distance to landslide locations were extracted from them and prepared as GIS layers. Multi-criteria and fuzzy decision-making methods were used to manage uncertainty and weight the criteria. Two modes, including a fuzzy model with OR and AND operators, were used. The classification results show that based on the fuzzy OR operator, the area of suitable areas for runway construction is 4.30 km2 and unsuitable areas are 6.10 km2. Based on the fuzzy AND operator, the area of suitable areas is 0.87 km2 and unsuitable areas are 9.53 km2. Comparison of the models reveals that the choice of fuzzy operator has a significant impact on the extent of suitable areas and the AND model provides a more conservative result. The findings also show that the slope, elevation, and aspect factors with coefficients of 0.28, 0.20, and 0.12, respectively, play the most role in determining suitability. This study suggests that a hybrid framework be used for final decision-making; initial safe areas are identified with the AND model and then supplemented with the OR results and field visit for final selection. The research results can provide clear guidance for local planners in selecting safe and efficient sites for developing ski resort infrastructure.
 
Extended Abstract
 
Introduction
Natural, social, cultural, and economic factors play a significant role in shaping settlement patterns and infrastructure siting, while advances in remote sensing (RS) and geographic information systems (GIS) have facilitated the integration of topographic, hydrological, and land-use data for more precise spatial decision-making. In this context, multicriteria decision-making methods, particularly fuzzy logic, enhance the reliability of site suitability assessments by providing systematic criteria weighting, addressing uncertainty, and defining flexible boundaries between suitable and unsuitable areas. In Kurdistan Province and Sanandaj, the lack of a standardized ski resort has encouraged the use of mountain passes and roads during snowy periods, increasing the risks of traffic accidents, avalanches, and injuries, while informal ski tracks may contribute to vegetation degradation, soil erosion, slope instability, and long-term socioeconomic costs. Previous studies indicate that integrating digital elevation models, topographic indices, climatic and geological data within a GIS framework, together with multicriteria decision-making and fuzzy logic, provides an effective approach for identifying suitable ski resort locations. Accordingly, this study evaluates Mount Abidar in Sanandaj using a set of environmental criteria and compares the fuzzy AND and OR operators. The AND operator generates more conservative and restricted suitability zones, whereas the OR operator produces broader suitable areas. The findings provide an operational framework for ski resort site selection, risk reduction, environmental protection, and sustainable tourism development in mountainous regions.
 
Methodology
The study area encompasses Mount Abidar on the outskirts of Sanandaj, with a maximum elevation of approximately 2,364 m and a total area of about 10.4 km². The mountainous terrain is characterized by variable slopes, valleys, and a semi-arid montane climate with snowy winters, providing favorable conditions for winter tourism and recreational activities while influencing slope stability and snow persistence. Spatial datasets included an ALOS PALSAR digital elevation model for extracting elevation, slope, aspect, and drainage networks; Sentinel-2 imagery acquired on February 22, 2024, for mapping roads and land use; and official geological maps for identifying faults and lithological units. Additional layers comprised river and road distance and density, landslide-prone areas, and potential emergency shelter locations. The datasets were clipped, reprojected, reclassified, and quality-controlled using authoritative sources and field verification. A GIS-based fuzzy logic approach was then applied, with criteria selected and weighted based on expert judgment and previous studies. Appropriate fuzzy membership functions standardized the spatial criteria into continuous suitability values. Finally, the fuzzy layers were integrated using the minimum (AND) and maximum (OR) operators. The AND operator represented a conservative, risk-averse approach, whereas the OR operator provided a more permissive suitability assessment. The resulting maps identified spatially prioritized areas suitable for further field verification and socioeconomic assessment for ski resort development.
 
Results and Discussion
The input layers were classified into five categories using the Natural Breaks (Jenks) method in ArcGIS 10.5 and normalized according to ski-site suitability criteria. Topographic factors, particularly slope, elevation, and aspect, exerted the greatest influence on suitability, with northern aspects considered more favorable because of lower solar radiation and greater snow retention. Land-use analysis indicated greater development in the lower and eastern sectors, while western and higher slopes remained less developed. Geological assessment identified two lithological units, with flysch receiving a higher suitability weight due to its greater relative competence. Fault-distance analysis also indicated generally more favorable conditions in the southern sectors. Fuzzy analysis revealed substantial differences between aggregation rules. The conservative minimum (AND) operator classified 9.53 km² as unsuitable and only 0.87 km² as suitable for ski-piste development, whereas the permissive maximum (OR) operator identified approximately 4.30 km² as suitable and 6.10 km² as unsuitable. These differences demonstrate the strong influence of aggregation rules and membership functions on suitability outcomes and represent a major source of uncertainty. Accordingly, the AND model is recommended for identifying priority low-risk areas, while the OR model can be used to expand candidate zones for further investigation. Final site selection should incorporate field validation, updated high-resolution elevation data, and safety constraints related to faults, hydrology, landslides, land-use compatibility, and emergency access.
 
Conclusion
Fuzzy logic implemented within a GIS environment effectively identifies and prioritizes suitable and unsuitable zones for ski piste development on Abidar Mountain. Twelve environmental and infrastructural criteria (including slope, elevation, aspect, geology, distance from faults, hydrological networks, roads and shelter proximity) were integrated using standardized fuzzy membership functions. Comparative results show that the aggregation rule substantially determines suitability extent: the AND operator produced a conservative suitable area of approximately 0.87 km², whereas the OR operator yielded a larger suitable area of approximately 4.30 km²—underscoring the need for parametric sensitivity and uncertainty analysis. A phased decision making algorithm is recommended: first adopt the conservative AND output to identify priority safety zones, then evaluate OR identified candidate areas through field inspection, socio economic assessment, and infrastructure planning. High DEM accuracy, rigorous field validation, and stakeholder engagement are critical to ensure safety, environmental sustainability, and social acceptance. The proposed RS–GIS–fuzzy framework offers a practical tool to support local planning and can be generalized to other areas exposed to hydrological and landslide hazards, provided outputs are complemented by environmental impact assessments, economic social appraisals, and participatory processes.