Department of Geography, Munzur University, Tunceli, Turkey.
Department of Emergency Aid and Disaster Management, Munzur University, Tunceli, Turkey.
Environ Sci Pollut Res Int. 2023 Nov;30(53):113978-114000. doi: 10.1007/s11356-023-30200-9. Epub 2023 Oct 19.
Landslides are among the most destructive geological disasters that seriously damage human life and infrastructures. Landslides mainly occur in mountainous regions around the world. One of the key processes to reduce these damages is to uncover landslide-exposed areas through different data-driven methods such as Geographical Information System (GIS) and multi-criteria decision-making (MCDM). In the literature, there are many studies developed with these fundamental tools. In this study, unlike the literature, a new landslide susceptibility assessment model is proposed by integrating GIS with the stratified best-worst method (S-BWM). This model has four main dimensions and 16 sub-dimensions under topography, environment-land, location, and hydrological factors, weighted with the S-BWM. A network was created considering the different states that may arise in the importance weights of these dimensions in the future. The transition probabilities of these states were predicted and injected into the classical BWM. Then, maps were created for these dimensions and classifications for each sub-dimension according to the map characteristics. Finally, the most susceptive landslide locations were determined with GIS-based calculations. To demonstrate the model's applicability, a case study was conducted for the Erzurum region, one of Turkey's landslide-prone regions. In addition, besides the landslide map, an analysis and discussion about the spatial distribution of susceptibility classes was presented, contributing to the study's robustness. In the results of landslide susceptibility analysis, landslides are higher in the range of about 1600-2500 m. Approximately 42% (35.59 sq. km) of the study area has high landslide susceptibility, while 58% (64.41 sq. km) has medium and low landslide susceptibility.
滑坡是最具破坏性的地质灾害之一，严重破坏人类生命和基础设施。滑坡主要发生在世界各地的山区。减少这些破坏的关键过程之一是通过地理信息系统（GIS）和多准则决策（MCDM）等不同数据驱动方法揭示滑坡暴露区域。在文献中，有许多使用这些基本工具开发的研究。在本研究中，与文献不同，通过将 GIS 与分层最佳最差方法（S-BWM）集成，提出了一种新的滑坡敏感性评估模型。该模型有四个主要维度和 16 个子维度，分为地形、环境-土地、位置和水文因素，由 S-BWM 加权。创建了一个网络，考虑了这些维度的重要性权重在未来可能出现的不同状态。预测了这些状态的转移概率，并将其注入到经典的 BWM 中。然后，根据地图特征为这些维度创建地图，并为每个子维度进行分类。最后，利用 GIS 计算确定最敏感的滑坡位置。为了证明该模型的适用性，对土耳其易发生滑坡的埃尔祖鲁姆地区进行了案例研究。此外，除了滑坡图之外，还对敏感性类别进行了空间分布的分析和讨论，有助于研究的稳健性。在滑坡敏感性分析结果中，在约 1600-2500 m 的范围内滑坡较高。研究区约有 42%（35.59 平方公里）具有高滑坡敏感性，而 58%（64.41 平方公里）具有中低滑坡敏感性。
