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高校地质学报 ›› 2025, Vol. 31 ›› Issue (05): 535-551.DOI: 10.16108/j.issn1006-7493.2024073

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基于灰色关联度模型和地理探测器的滑坡因子筛选及易发性评价

谢贤健,吴 汉,许 斌,吕奕葳   

  1. 内江师范学院 地理与资源科学学院,内江 641112
  • 出版日期:2025-10-20 发布日期:2025-10-20

Slope Factor Screening and Susceptibility Assessment Based on the Grey Relational Degree Model and Geographic Detector

XIE Xianjian,Wu Han,Xu Bin,LYU Yiwei   

  1. School of Geography and Resources Science of Neijiang Normal University, Neijiang 641112, China
  • Online:2025-10-20 Published:2025-10-20

摘要: 滑坡因子筛选及易发性评价在减少滑坡灾害风险、优化国土空间利用、保护生态环境、促进科学研究以及提升政府灾害管理能力等领域具有重要意义。文章首先从地形与基础地质因子和水文环境、地表覆被及社会经济因子两方面构建滑坡易发性数据库,再基于GIS技术,利用主成分、灰色关联度模型、地理探测器方法和变异系数法诊断出影响小江流域促发滑坡易发性的关键因子,同时利用空间分析中的加权叠加工具,对研究区滑坡易发性进行综合性评价。结果表明,研究区极高、高、中等、低、极低易发区的面积比例为9.91∶21.90∶29.76∶26.00∶12.43;对研究区176个不同等级的滑坡类型进行了验证,占流域总面积31.81%的高、极高易发性区域分布了大型和特大型滑坡总和的75.76%,中小型滑坡全部分布在中等、低、极低易发区,低、极低易发区少有分布大型和特大型滑坡;利用灰色关联度模型、地理探测器方法筛选出的15个滑坡关键因子对滑坡易发性进行评价,其结果符合实际情况,证实了方法的正确性,可以为研究区滑坡易发性评价提供科学支撑。

关键词: 滑坡易发性, 因子筛选, 地理信息系统, 小江流域

Abstract: Slope factor screening and susceptibility assessment play a significant role in reducing landslide disaster risks, optimizing land use, protecting ecological environments, advancing scientific research, and enhancing governmental disaster management capabilities. This study first constructs a landslide susceptibility database considering two aspects: terrain and basic geological factors, as well as hydrological environment, surface cover, and socioeconomic factors. Then, utilizing GIS technology, it employs principal component analysis, grey relational analysis, geographic detector methods, and the coefficient of variations to diagnose the critical factors influencing landslide susceptibility in the Xiaojiang River Basin. In addition, it uses the weighted overlay tool in spatial analysis to conduct a comprehensive assessment of landslide susceptibility in the study area. The results indicate that the area proportions of extremely high, high, moderate, low, and extremely low susceptibility zones in the study area are 9.91:21.90:29.76:26.00:12.43, respectively. Verification was conducted on 176 different grades of landslide types in the study area, and 75.76% of the total number of large and mega-sized landslides are distributed within the high and extremely high susceptibility zones, which together cover 31.81% of the basin’s total area. Small and medium-sized landslides are entirely distributed in the moderate, low, and extremely low susceptibility zones, with few large and mega-sized landslides found in the low and extremely low susceptibility areas. The evaluation of landslide susceptibility using 15 critical factors, selected by the grey relational analysis model and the geographic detector method, agrees with the real-world conditions. This confirms the accuracy of the methods and can provide a scientific basis for landslide susceptibility assessment in the study area.

Key words: landslide susceptibility, factor screening, Geographic Information System, Xiaojiang River basin