桂林市滑坡灾害易发性评价及致灾因子探测分析

doi:10.16088/j.issn.1001-6600.2025091701

摘要/Abstract

摘要： 科学精细的滑坡易发性空间分布图可为滑坡灾害防治及社会基础设施建设与规划提供重要依据。本文基于752组历史滑坡数据记录,综合运用基于频率比的信息量模型与GIS层次分析模型开展滑坡易发性评价,编制了30 m分辨率的桂林市滑坡灾害易发性分区图。进而借助地理探测器,通过与断裂带距离、降水量、坡度、高程、人口分布、地层岩性、坡向、归一化植被指数(NDVI)、与水系距离、与道路距离10个评价因子对桂林市滑坡灾害的易发性进行解释力分析。研究结果表明:1)桂林市滑坡灾害易发性空间分布呈现南高北低的空间分异格局;2)全市整体滑坡灾害易发性水平较高、极高与高易发区占比超50%以上;3)单因子探测分析显示,地层岩性对滑坡易发性影响最为显著,各因子交互作用表现为非线性增强与双因子增强关系,其中地层岩性与降水量的交互作用解释力最强(14.91%)。本研究所采用的模型均能有效评估滑坡灾害易发性,并提升分析精度,多模型联合应用既避免了单一评价方法的片面性,也为其他区域滑坡灾害评估与防治提供方法参考。

关键词: 滑坡, 易发性, 致灾因子, 信息量模型, 地理探测器, 桂林市

Abstract: Scientifically precise spatial distribution maps of landslide susceptibility provide an important basis for landslide disaster prevention and control, as well as the construction and planning of social infrastructure. Based on 752 sets of historical landslide data, this study comprehensively applied an information value model using frequency ratios and an AHP-GIS model to conduct a landslide susceptibility assessment, ultimately producing a 30 m-resolution landslide susceptibility zoning map for Guilin City. Furthermore,with the help of geographical detector, an explanatory power analysis was conducted on ten evaluation factors: distance to faults, precipitation, slope, elevation, population distribution, lithology, aspect,normalized difference vegetation index (NDVI), distance to water systems, and distance to roads, to assess their influence on landslide susceptibility in Guilin City. The research results indicate that:1) The spatial distribution of landslide susceptibility in Guilin exhibits a pattern of higher susceptibility in the south and lower in the north; 2) The overall level of landslide susceptibility in the city is relatively high, with extremely high and high susceptibility areas accounting for over 50% of the total; 3) Single-factor detection analysis shows that lithology has the most significant impact on landslide susceptibility, while the interaction of factors exhibits nonlinear enhancement and two-factor enhancement relationships. Among these, the interaction between lithology and precipitation has the strongest explanatory power (14.91%). The models used in this study effectively assess landslide susceptibility and improve analytical accuracy. The combined application of multiple models not only avoids the one-sidedness of a single evaluation method but also provides a methodological reference for landslide disaster assessment and prevention in other regions.

Key words: landslide, susceptibility, causative factors, information model, geodetector, Guilin City, China

中图分类号: P642.22

贾艳红, 李新静, 唐时宇. 桂林市滑坡灾害易发性评价及致灾因子探测分析[J]. 广西师范大学学报（自然科学版）, 2026, 44(5): 151-167.

Jia Yanhong, Li Xinjing, Tang Shiyu. Evaluation of landslide susceptibility and analysis of disaster-causing factor detection in Guilin City, China[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 151-167.

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