1.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
2.成都理工大学环境与土木工程学院,四川 成都,610059
张明钰,硕士生,主要从事边坡失稳破坏与宏观形变特征对应关系研究。mingyu11zhang@163.com
郑光,博士,高级实验师。flywing140@163.com
收稿:2024-10-26,
纸质出版:2025-06-05
移动端阅览
张明钰,郑光,刘震东,等.堆积体滑坡内部变形与表层宏观形变特征的对应耦合关系及其应用[J].武汉大学学报(信息科学版),2025,50(6):1235-1250.
ZHANG Mingyu,ZHENG Guang,LIU Zhendong,et al.Coupling Mechanism Between Internal Deformation and Macroscopic Deformation Characteristics of Accumulation Landslides and Its Application[J].Geomatics and Information Science of Wuhan University,2025,50(6):1235-1250.
张明钰,郑光,刘震东,等.堆积体滑坡内部变形与表层宏观形变特征的对应耦合关系及其应用[J].武汉大学学报(信息科学版),2025,50(6):1235-1250. DOI:10.13203/j.whugis20240345
ZHANG Mingyu,ZHENG Guang,LIU Zhendong,et al.Coupling Mechanism Between Internal Deformation and Macroscopic Deformation Characteristics of Accumulation Landslides and Its Application[J].Geomatics and Information Science of Wuhan University,2025,50(6):1235-1250. DOI:10.13203/j.whugis20240345
综合遥感技术可以捕捉滑坡地表变形迹象,但无法准确获得斜坡内部变形特征,从而限制了其评估当前斜坡所处阶段或滑动风险的能力。为克服这一问题,开展大型离心模型试验,利用多角度相机和图像处理技术收集堆积体斜坡地表和内部的变形数据,建立内部变形和宏观变形特征之间的联系。利用合成孔径雷达和激光雷达等技术,为早期滑坡识别提供了一个半定量框架。研究表明,滑坡后缘的裂缝水平延伸,形成出现近似平行于坡体走向的弧形拉裂缝的发展趋势;堆积体滑坡破坏通常始于坡顶,由后向前逐步发展。所提的滑坡阶段划分方法将位移-加速度曲线与土壤的超固结比相结合,以超固结比突变点为界,突变前为土体固结沉降阶段以及应力重分布阶段,突变后为斜坡发生破坏阶段。选取两个典型案例进行对比分析,证明运用模型试验结果可以提高遥感技术识别滑坡变形阶段的能力,使用堆积体滑坡内部形变与表层形变特征的对应图谱对利用遥感解译结果判释滑坡体的变形阶段有一定的指导意义。
Objectives
2
Integrated remote sensing technology primarily captures deformation indicators on the surface of the slope but fails to delineate the internal deformation characteristics clearly. Consequently
it can only facilitate preliminary identification without accurately determining the current stage of the slope or assessing the risk of sliding.
Methods
2
To investigate these issues
a centrifugal model test of a large-scale accumulation landslide was performed. Deformation characteristic data for both the surface and interior of the slope were obtained through multi-angle imaging
image processing
and observational deduction. This approach established a correlation between the internal deformation and the macroscopic deformation characteristics of the accumulation landslide. The resulting data provide a semi-quantitative reference framework for the early identification and warning of landslides using technologies such as aperture radar
light detection and ranging
and optical remote sensing to ascertain the deformation stage of landslides.
Results
2
The results show that during the development of the accumulation landslide
cracks at the trailing edge extend significantly in the horizontal direction
while cracks on the back wall exhibit an arc-shaped tensile development trend
approximately parallel to the slope's alignment. Slip failure in homogeneous soil slopes typically initiates at the slope crest
with overall failure occurring as the sliding surface gradually advances from back to front. A novel method for classifying landslide stages is proposed
which combines the displacement-acceleration curve of the accumulation landslide with the soil's over-consolidation ratio. A sudden change in the over-consolidation ratio serves as a segmentation point
with the soil consolidation settlement stage and stress redistribution stage preceding the change
and the slope failure stage following it.
Conclusions
2
By comparing and analyzing typical cases
the results indicate that model test outcomes can aid remote sensing technology in distinguishing the deformation stages of landslides for early identification. This suggests that utilizing the correspondence mapping between the internal deformation of the accumulation landslide and the surface deformation characteristics offers valuable guidance for interpreting the deformation stage of the landslide through remote sensing.
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