考虑滑坡类型耦合方式的滑坡易发性预测建模与不确定性分析

贾卓; 程志金; 常志璐; 李琴; 彭宇豪; 江炳辰; 黄发明

doi:10.3799/dqkx.2025.008

Volume 50 Issue 6

Jun. 2025

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Article Navigation > Earth Science > 2025 > 50(6): 2311-2329

Jia Zhuo, Cheng Zhijin, Chang Zhilu, Li Qin, Peng Yuhao, Jiang Bingchen, Huang Faming, 2025. Modeling and Uncertainty in Landslide Susceptibility Prediction Considering Coupling Mode of Landslide Types. Earth Science, 50(6): 2311-2329. doi: 10.3799/dqkx.2025.008

Citation:

Jia Zhuo, Cheng Zhijin, Chang Zhilu, Li Qin, Peng Yuhao, Jiang Bingchen, Huang Faming, 2025. Modeling and Uncertainty in Landslide Susceptibility Prediction Considering Coupling Mode of Landslide Types. Earth Science, 50(6): 2311-2329. doi: 10.3799/dqkx.2025.008

Citation:

Jia Zhuo, Cheng Zhijin, Chang Zhilu, Li Qin, Peng Yuhao, Jiang Bingchen, Huang Faming, 2025. Modeling and Uncertainty in Landslide Susceptibility Prediction Considering Coupling Mode of Landslide Types. Earth Science, 50(6): 2311-2329. doi: 10.3799/dqkx.2025.008

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Modeling and Uncertainty in Landslide Susceptibility Prediction Considering Coupling Mode of Landslide Types

doi: 10.3799/dqkx.2025.008

Jia Zhuo^{1
,
,},
Cheng Zhijin¹,
Chang Zhilu^{2
,
,},
Li Qin³,
Peng Yuhao¹,
Jiang Bingchen¹,
Huang Faming^{1
,
,}

1.
School of Infrastructure Engineering, Nanchang University, Nanchang 330031, China
2.
School of Resources & Environment, Nanchang University, Nanchang 330031, China
3.
Institute of Energy Research, Jiangxi Academy of Sciences, Nanchang 330096, China

Received Date: 2024-09-28
Publish Date: 2025-06-25

Abstract

Abstract

In order to comprehensively consider the differences between different types of landslides, improve the accuracy and engineering application value of landslide susceptibility prediction, taking Wanzhou District, Chongqing City as an example, support vector machine, C5.0 decision tree, logistic regression, and multilayer perceptron models were applied to model the susceptibility of a single stacked layer landslide and rockfall. Based on the optimal comprehensive performance model, direct coupling method, probability statistics method, and susceptibility comparison method were used to couple and model different types of landslides, and their uncertainties were evaluated. The results show that the C5.0 decision tree model performs best in susceptibility prediction for single-type landslides, with AUC values exceeding 0.930. The susceptibility prediction results of the three coupling methods are generally consistent with the actual situation, among which the comparative susceptibility method exhibits higher AUC values and accuracy in frequency ratio, demonstrating the best predictive performance. The probabilistic statistical method ranks second, followed by the direct coupling method. In terms of comprehensively reflecting the evolution patterns of landslides, adapting to actual scenarios, and supporting prevention and control decisions, considering the coupling of landslide types yields better landslide susceptibility predictions than considering only single-type landslides. However, it is still necessary to explore the specificity among different types of landslides and optimize coupling methods in greater depth in the future.
- landslide susceptibility,
- different types of landslide,
- coupling method,
- uncertainty analysis,
- machine learning,
- engineering geology

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References(54)

References

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Modeling and Uncertainty in Landslide Susceptibility Prediction Considering Coupling Mode of Landslide Types

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