ArticleScientific reports2025
Study on comprehensive landslide risk zoning method in open pit mines under multi factor coupling effects.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Multi-Modal Data-Driven Bayesian-Optimized CNN-LSTM Model for Slope Displacement Prediction.Sensors (Basel, Switzerland) · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
Comprehensive landslide risk zoning in open-pit mines is fundamental to precise safety monitoring, early warning, and disaster prevention and control. Existing approaches often rely on single static indicators and exhibit limited capacity for dynamic risk regulation. To address these limitations, this study proposes a scientifically grounded slope zoning method that couples multiple factors across "engineering-geological-environmental (seasonal variations, distribution of infrastructure)". First, a hierarchical structure model comprising four key influencing degree of crack development, slope angle, slope height, and rock and soil properties-is constructed using the Analytic Hierarchy Process (AHP). By computing the weight coefficients of these evaluation indices and deriving a slope hazard index, we classify slope hazard zones. Additionally, the two-dimensional rigid-body Limit Equilibrium Method (LEM) is applied to calculate slope factor of safety for multiple cross-sections, facilitating the delineation of slope stability zones. To integrate these results, we employ a combined cross-matrix analysis and simple weighted averaging method, further refining the comprehensive risk zoning by dynamically incorporating factors such as slope along-strike surface shape, seasonal (climatic) variations, fault characteristics, and distribution of infrastructure. This approach is validated through application to a case study in an open-pit mine, where one higher-risk, five medium-risk, and six low-risk zones are identified. Notably, the higher-risk zone exhibits strong spatial agreement with actual landslide occurrences. The results demonstrate that the proposed method significantly enhances zoning accuracy, providing a theoretical basis for the optimized allocation of monitoring resources, the development of differentiated early-warning models, and the full-lifecycle management of slopes in open-pit mining operations.
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Registered trials
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