Sürdürülebilir Kalkınma Amaçları

• 1
• 1
• 1

Yazarlar

• Atasoy, M.(1)
• Bayrak, T.(1)
• Ekercin, S.(1)
• Eraslan, Selim(1)
• Erduran, M.(1)
• Işık, Fatih(1)
• Kanyılmaz, Rabia(1)
• Nisanci, R.(1)
• Reis, S.(1)
• Sancar, C.(1)
• Yalcin, A.(1)
• Zeybek, Halil İbrahim(1)
• Çağlak, Savas(1)

• MakaleAçık Erişim2025/r/gumushane/13794
  Spatially explicit modeling of road icing susceptibility using GIS and a multi-criteria decision approach: A case study of Gümüşhane city (Türkiye)

  Işık, Fatih; Kanyılmaz, Rabia; Çağlak, Savas; Eraslan, Selim; Zeybek, Halil İbrahim

  This study develops and validates a GIS-based, spatio-temporal model to identify and prioritize road segments with high icing susceptibility in the Gümüşhane city center, Türkiye. Icing on urban roadways constitutes a significant threat to vehicular and pedestrian safety, particularly in regions characterized by complex topography and dense urban morphology. A Multi-Criteria Decision Analysis (MCDA) framework, employing the Analytic Hierarchy Process (AHP) with structured expert input, was used to synthesize ten primary causative factors. These include solar radiation, temperature, aspect, object height, precipitation, elevation, pavement material, slope, albedo, and road width — each representing a distinct topographic, climatic, or morphological influence on urban road icing. The AHP quantitatively established the relative influence of these factors, identifying solar radiation (28.5%), temperature (18.2%), and aspect (13.5%) as the most dominant drivers. The model generates monthly susceptibility maps that reveal "urban canyons"—narrow streets flanked by highrise buildings—consistently exhibit the highest and most persistent susceptibility due to severely limited solar radiation. The accuracy of the model's spatial predictions was quantitatively validated through field observations, with 91.4% of recurring icing locations correctly identified within high or very high susceptibility zones. This research culminates not only in a robust scientific framework but also in a validated decision-support tool that has been successfully integrated into the Gümüşhane City Information System (GCIS), where it is now operationally used to optimize winter maintenance strategies. Ultimately, this work provides a replicable, data-driven approach for enhancing urban resilience and traffic safety in challenging topographical settings.

  • 
  • 
  • 
  İncele
• MakaleYalnız künye2012/r/gumushane/13206
  Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio and analytical hierarchy methods in Rize province (NE Turkey)

  Reis, S.; Yalcin, A.; Atasoy, M.; Nisanci, R.; Bayrak, T.; Erduran, M.; Sancar, C.; Ekercin, S.

  The northeast part of Turkey is prone to landslides because of the climatic conditions, as well as geologic and geomorphologic characteristics of the region. Especially, frequent landslides in the Rize province often result in significant damage to people and property. Therefore, in order to mitigate the damage from landslides and help the planners in selecting suitable locations for implementing development projects, especially in large areas, it is necessary to scientifically assess susceptible areas. In this study, the frequency ratio method and the analytical hierarchy process (AHP) were used to produce susceptibility maps. Especially, AHP gives best results because of allowing better structuring of various components, including both objective and subjective aspects and comparing them by a logical and thorough method, which involves a matrix-based pairwise comparison of the contribution of different factors for landslide. For this purpose, lithology, slope angle, slope aspect, land cover, distance to stream, drainage density, and distance to road were considered as landslide causal factors for the study area. The processing of multi-geodata sets was carried out in a raster GIS environment. Lithology was derived from the geological database and additional field studies; slope angle, slope aspect, distance to stream, distance to road and drainage density were invented from digital elevation models; land cover was produced from remote sensing imagery. In the end of study, the results of the analysis were verified using actual landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

  İncele