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从印度西高止山脉湿润的热带地区,运用模糊层次分析法对滑坡易发性进行建模的集成方法。

Ensemble of fuzzy-analytical hierarchy process in landslide susceptibility modeling from a humid tropical region of Western Ghats, Southern India.

机构信息

Department of Climate Variability and Aquatic Ecosystems, Kerala University of Fisheries and Ocean Studies (KUFOS), Kochi, Kerala, 682508, India.

Department of Environmental Studies, Kannur University, Kannur, 670567, India.

出版信息

Environ Sci Pollut Res Int. 2024 Jun;31(29):41370-41387. doi: 10.1007/s11356-023-27377-4. Epub 2023 May 9.

DOI:10.1007/s11356-023-27377-4
PMID:37156952
Abstract

The western flanks of the Western Ghats are one of the major landslide hotspots in India. Recent rainfall triggered landslide incidents in this humid tropical region necessitating the accurate and reliable landslide susceptibility mapping (LSM) of selected parts of Western Ghats for hazard mitigation. In this study, a GIS-coupled fuzzy Multi-Criteria Decision Making (MCDM) technique is used to evaluate the landslide-susceptible zones in a highland segment of the Southern Western Ghats. Fuzzy numbers specified the relative weights of nine landslide influencing factors that were established and delineated using the ArcGIS, and the pairwise comparison of these fuzzy numbers in the Analytical hierarchy process (AHP) system resulted in standardized causative factor weights. Thereafter, the normalized weights are assigned to corresponding thematic layers, and finally, a landslide susceptibility map is generated. The model is validated using the area under the curve values (AUC) and F1 scores. The result reveals that about 27% of the study area is classified as highly susceptible zones followed by 24% area in moderately susceptible zone, 33% in low susceptible, and 16% in a very low susceptible area. Also, the study shows that the plateau scarps in the Western Ghats are highly susceptible to the occurrence of landslides. Moreover, the predictive accuracy estimated by the AUC scores (79%) and F1 scores (85%) shows that the LSM map is trustworthy for future hazard mitigation and land use planning in the study area.

摘要

西高止山脉的西坡是印度主要的滑坡多发区之一。最近的降雨在这个潮湿的热带地区引发了滑坡事件,因此需要对西高止山脉的选定地区进行准确可靠的滑坡易发性制图(LSM),以减轻灾害。本研究采用 GIS 耦合模糊多准则决策分析(MCDM)技术,对西高止山脉南段的一个高地地段进行滑坡易发性分区。模糊数指定了九个滑坡影响因素的相对权重,这些因素是使用 ArcGIS 建立和划定的,在层次分析法(AHP)系统中对这些模糊数进行成对比较,得出标准化的致灾因子权重。然后,将归一化权重分配给相应的专题图层,最终生成滑坡易发性图。该模型通过曲线下面积值(AUC)和 F1 分数进行验证。结果表明,研究区约 27%的区域被划分为高度易发性区,其次是中度易发性区(24%)、低度易发性区(33%)和极低易发性区(16%)。此外,研究表明,西高止山脉的高原峭壁极易发生滑坡。此外,AUC 得分(79%)和 F1 得分(85%)估计的预测精度表明,LSM 图对于研究区未来的灾害减轻和土地利用规划是可靠的。

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