基于多源遥感数据采动滑坡动态演变特征分析研究

严浩元; 冯瀚; 解明礼; 刘哲延

doi:10.11932/karst20250611

基于多源遥感数据采动滑坡动态演变特征分析研究——以尖山营滑坡为例

doi: 10.11932/karst20250611

1.
贵州省第一测绘院, 贵州贵阳 550025
2.
成都理工大学地质灾害防治与地质环境保护国家重点实验室, 四川成都 610059

基金项目: 地质灾害防治与地质环境保护国家重点实验室开放基金资助项目(SKLGP2024K030)

详细信息

作者简介:
严浩元（1994－），男，硕士，工程师，主要从事地质灾害综合遥感监测与调查。E-mail：599048446@qq.com

通讯作者:
冯瀚（1996－），男，硕士，工程师，主要从事InSAR地表形变监测。E-mail：Hanfeng709@126.com。

中图分类号: P237；P642.22
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出版历程
- 收稿日期: 2025-01-20
- 录用日期: 2025-07-21
- 修回日期: 2025-07-10
- 刊出日期: 2025-12-25

Analysis of dynamic evolution characteristics of mining-induced landslide based on multi-source remote sensing data: A case study of Jianshanying landslide

1.
Guizhou Provincial First Institute of Surveying and Mapping, Guiyang , Guizhou 550025, China
2.
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059, China

摘要

摘要: 采动滑坡具有变形破坏机制复杂、时间长的特点，对山体地质环境造成不可逆损害，是近年来地质灾害研究的重要课题。传统的地表位移监测很难大范围推广到采动滑坡中，这给采动滑坡的监测预警带来了难题。本文采用空–天–地一体化的手段，多维度分析了尖山营滑坡历史的动态变化特征。研究表明：尖山营滑坡这类多煤层重复采动的采矿滑坡具有变形大的特征，在长期开采和降雨的作用下于易发生滑坡；多期次光学遥感影像和无人机影像对比分析可得出滑坡不同位置随时间变化的宏观变形差异；长时间序列合成孔径雷达能够较为准确地获取地表形变的时空演化规律；机载LiDAR获取的地表点云信息可直观获取滑坡的高程变化和微地貌变化特征，以上遥感手段结合现场实际调查、滑坡工程地质条件和开采条件进行综合研判，最终得出滑坡动态演化特征分析和形成机制，以期为类似的多煤层重复采动的采矿滑坡识别预警和防治提供一定参考。
- 多源遥感 /
- 采动滑坡 /
- 动态演变 /
- 地表变形 /
- 多源融合分析
Abstract: Landslides occurring on mountain slopes due to deformation and failure of overlying rock masses under the influence of underground mining activities are referred to as mining-induced landslides. Slopes exhibiting deformation caused by such activities but have not yet experienced sliding failure are classified as mining-induced slopes. Mining-induced landslides are characterized by complex deformation and failure mechanisms, as well as prolonged development periods. They cause irreversible damage to the mountain geological environment. These slopes often undergo extended periods of stress adjustment and deformation evolution, leading to the formation of numerous mining-induced fractures within the slope mass. Simultaneously, multiple collapse troughs and subsidence basins develop on the slope surface, significantly reducing the integrity of the rock mass. Under favorable free-face conditions at the front of a slope, sudden-onset geological disasters are highly likely to occur. Mining landslides represent a critical area of research on geological hazards. Analyzing both their surface deformation and historical deformation holds significant importance for the identification and early warning of mining-induced landslides. In recent years, to facilitate convenient and intuitive identification, investigation, and monitoring of geological hazards, technologies such as Spaceborne Interferometric Synthetic Aperture Radar (InSAR), high-resolution optical satellite imagery, Unmanned Aerial Vehicle (UAV) aerial photography, and Airborne Light Detection and Ranging (LiDAR) have been widely used. Notably, combining space-borne, airborne, and ground-based platforms facilitates multi-method, multi-scale, and long-term monitoring of the deformation and failure characteristics of geological hazards. This integrated approach addresses a critical need and represents a key direction for advancing early identification, and disaster prevention and mitigation of landslide hazards. Jianshanying landslide is located in Fa’er Town, Liupanshui City, Guizhou Province. The landslide site has experienced deformation for many years due to repeated multi-seam mining operations. Ultimately, it slid in September 2020 as a result of the combined effects of long-term mining activities and rainfall. This landslide is a typical example of mining landslide occurring in the karst terrain in Guizhou Province. This study adopts an integrated space-air-ground approach to conduct a multi-dimensional analysis of the historical dynamic changes of Jianshanying landslide. Research shows that mining-induced landslides like Jianshanying landslide, caused by repeated multi-seam mining, exhibit significant deformation magnitudes. Prolonged mining activities combined with rainfall increase the susceptibility to landslides. Comparative analysis of multi-temporal optical remote sensing imagery and UAV data can reveal the macro-scale deformation variations at different locations of the landslide over time. Long time-series Synthetic Aperture Radar (InSAR) technology can accurately capture the spatio-temporal evolution patterns of surface deformation. Additionally, surface point cloud data acquired by airborne LiDAR can provide detailed information on elevation changes and micro-geomorphological characteristics of the landslide. Through a comprehensive interpretation of the aforementioned remote sensing means, combined with field investigations and analysis of the landslide’s engineering geological and mining conditions, the following conclusions are established: as early as before 2013, Jianshanying landslide exhibited relatively obvious disaster features, such as the main scarp, landslide boundaries, and terraces. With the progression of mining activities, by 2016, Jianshanying landslide gradually transformed from multiple deformation bodies into a single integrated mass. Rear tension cracks appeared around 2016 as visibly open fissures. After 2017, these cracks accelerated in both widening and extension. The entire mass displaced downward, resulting in local collapses. Ultimately, under the combined action of long-term repeated mining and rainfall, the landslide occurred in 2020. The deformation of Jianshanying landslide experienced four stages: caving-subsidence deformation, tensile cracking deformation, creep deformation, and shear sliding failure. From the perspective of movement mechanism, it is a typical retrogressive landslide (push-type landslide).
- multi-source remote sensing /
- mining-induced landslide /
- dynamic evolution /
- surface deformation /
- multi-source fusion analysis

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图 1 尖山营滑坡影像图

Figure 1. Three-dimensional image of Jianshanying deformed body

下载: 全尺寸图片幻灯片

图 2 尖山营滑坡历史变形特征

Figure 2. Historical deformation characteristics of Jianshanying landslide

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图 3 尖山营滑坡局部历史变形特征

Figure 3. Characteristics of local historical deformation of Jianshanying landslide

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图 4 研究区年平均形变速率

Figure 4. Average annual deformation rate in the study area

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图 5 尖山营滑坡时序变形

Figure 5. Time sequence deformation of Jianshanying landslide

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图 6 尖山营滑坡两期地形数据对比

Figure 6. Comparison of topographic data of Jianshanying landslide in two phases

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图 7 尖山营滑坡典型破坏特征

Figure 7. Typical failure characteristics of Jianshanying landslide

下载: 全尺寸图片幻灯片

图 8 尖山营滑坡演化模式图

Figure 8. Model diagram of Jianshanying landslide evolution

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