| 孙亚男,孙浩,高彦昆,李奇键.基于多源遥感与InSAR时序分析的矿山边坡稳定性动态评估与预警模型[J].矿产勘查,2026,17(S1):279-285 |
| 基于多源遥感与InSAR时序分析的矿山边坡稳定性动态评估与预警模型 |
| Dynamic evaluation and early warning model of mine slope stability based on multi-source remote sensing and InSAR time series analysis |
| 投稿时间：2026-01-23 修订日期：2026-03-25 |
| DOI：10.20008/j.kckc.2026S1032 |
| 中文关键词: 多源遥感 时序InSAR 边坡稳定性 动态评估 预警模型 矿山安全 |
| 英文关键词: multi-source remote sensing temporal InSAR slope stability dynamic assessment early warning model mine safety |
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| 中文摘要: |
| 针对矿山边坡稳定性监测中传统方法时空覆盖不足、预警滞后等问题，本文提出了一种融合多源遥感与时序InSAR技术的动态评估与预警模型。通过集成星载SAR（如Sentinel-1）、光学遥感和激光雷达等多源数据，采用SBAS-InSAR方法提取毫米级形变时序信息，结合地形、地质、水文及人类活动等多维因子，构建边坡稳定性动态评估指标体系。基于深度学习与时空演化分析，开发了能够识别失稳先兆的智能预警模型。以典型露天矿为例进行验证，结果表明该模型可有效提升隐患识别精度与预警时效性，为实现矿山边坡灾害风险的全过程动态管控提供了可行方法。 |
| 英文摘要: |
| To address the limitations of traditional methods in mine slope stability monitoring—such as inadequate spatiotemporal coverage and delayed early warnings—this study proposes a dynamic evaluation and early warning model integrating multi-source remote sensing and temporal InSAR technology. By synthesizing data from satellite-borne SAR （e.g.， Sentinel-1）， optical remote sensing， and LiDAR， the SBAS-InSAR method extracts millimeter-scale deformation temporal information. This is combined with multidimensional factors including topography， geology， hydrology， and human activities to establish a dynamic evaluation index system for slope stability. Leveraging deep learning and spatiotemporal evolution analysis， an intelligent early warning model capable of identifying instability precursors was developed. Validation using a typical open-pit mine demonstrated that the model significantly improves hazard identification accuracy and early warning timeliness， providing a practical approach for dynamic risk management throughout the entire lifecycle of mine slope disasters. |
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