A novel InSAR-based workflow for DEM-driven slope modeling and risk prediction
Year: 2025
Type: article
Abstract: Timely and accurate topographic modeling is essential for slope stability assessment and landslide risk prediction in open-pit mines. Traditional modeling methods often suffer from delayed terrain updates and weather limitations. This study proposes a novel integrated approach that combines an Interferometric Synthetic Aperture Radar (InSAR) derived digital elevation model (DEM) with finite difference numerical simulations to enable rapid modeling and predictive assessment of dump slope stability under intense drying-wetting cycles. A three-dimensional (3D) slope model was dynamically constructed using the InSAR DEM from 2022 to 2024, and numerical simulations were conducted based on coupled unsaturated-saturated seepage theory and shear strength reduction principles. A multi-parameter prediction model for the factor of safety (Fos) was developed by correlating it with the vertical displacement, dry-wet cycle number, and intensity. Simulation results show that surface saturation, pore water pressure, and vertical displacement increase cumulatively with cycle progression, whereas the Fos decreases yet remains above the stability threshold (Fos > 1.20). The proposed Fos model achieves good predictive performance with determination coefficients (R²) of 0.81 and 0.91 for two monitored dump slopes. These findings demonstrate the feasibility of a real-time ‘InSAR-modeling-prediction’ framework for landslide risk early warning in open-pit mining operations.
Authors: Jianjun Dong, Hao Jiang, Mingxin Xu, Ke Gao
Institution: Liaoning Technical University
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,790
Award: G7893145347
OpenAlex ID: W4417181005