长沙理工大学学报(自然科学版)
多源遥感揭示公路边坡变形与裂缝的耦合机制
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作者单位:

(1. 云南省公路科学技术研究院 , 云南 昆明 650051;2. 昆明理工大学 国土资源工程学院 , 云南 昆明 650093;3. 昆明理工大学 公共安全与应急管理学院 , 云南 昆明 650093)

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通讯作者:

袁利伟(1978—)(ORCID:0000-0002-7816-7404),男,教授,主要从事安全监测与监控方面的研究。E-mail:YuanLW@kust.edu.cn

中图分类号:

U416;P237;X951

基金项目:

国家自然科学基金项目(52364020);云南省公路科学技术研究院项目(4530000HT2024141190101)第一作者:李宁(1984—),男,高级工程师,主要研究从事公路防灾减灾方面的研究。E-mail:191509365@qq.com


Coupling mechanism of deformation and cracks in highway slopes revealed by multi -source remote sensing
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(1. Yunnan Provincial Academy of Highway Science and Technology , Kunming 650051, China; 2. Faculty of Land Resources Engineering , Kunming University of Science and Technology , Kunming 650093, China; 3. Faculty of Public Safety and Emergency Management , Kunming University of Science and Technology , Kunming 650093, China)

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    摘要:

    【目的】针对传统方法在复杂山区公路边坡滑坡识别中效率低、覆盖难的问题,探索一种高效精准的识别与机理分析方法。【方法】以云南省华宁县 G357线K2643 +617处典型滑坡为研究对象,采用永久散射体合成孔径雷达干涉测量 (persistent scatterer interferometric synthetic aperture radar,PS-InSAR)、机载激光雷达(light detection and ranging,LiDAR)与高分辨率光学遥感等多源技术,形成协同解译技术路径,充分发挥 PS-InSAR在毫米级形变监测、机载 LiDAR在植被穿透与微地貌精细刻画、光学遥感在边界快速解译方面的优势。【结果】滑坡体处于持续运动状态,最大累积形变量达 ?20 mm,年均形变速率达 ?8 mm·a?1;基于机载LiDAR数据精准识别出滑坡后缘及前缘 3条主要滑坡裂缝及 2条与既有抗滑桩空间位置重合的工程变形边界;形变 -裂缝空间叠加分析显示,高形变速率区 (形变速率为 [?8,?4.8) mm·a?1)与密集裂缝发育带高度重合,2条主要裂缝的主体部分都位于高形变速率区 (占比 66.7%),1条主要裂缝的主体部分位于中形变速率区 (形变速率为[1.6,4.8)及[?4.8,?1.6) mm·a?1);2条工程变形边界的主体部分均位于高形变速率区 (占比 100%),揭示了滑坡中前部为变形累积与应力集中的关键区域。【结论】该滑坡是以抗滑工程失效和降雨为诱发因素的牵引式复活滑坡,多源遥感协同技术可为滑坡灾害早期识别、机制剖析与风险防控提供关键的技术支撑。

    Abstract:

    [Purposes ] In view of the low efficiency and limited coverage of traditional methods in identifying landslides on highway slopes in complex mountainous areas,an efficient and accurate method for identification and mechanism analysis was explored in this paper.[Methods] By taking the typical landslide at K 2643 +617 on the G 357 line in Huaning County,Yunnan Province as the research object,multi -source technologies including persistent scatterer interferometric synthetic aperture radar (PS-InSAR),airborne light detection and ranging (LiDAR),and high -resolution optical remote sensing were integrated to form a technical pathway of collaborative interpretation.The advantages of PS -InSAR in millimeter -level deformation monitoring,airborne LiDAR in vegetation penetration and fine characterization of micro -topography,and optical remote sensing in rapid boundary interpretation were fully leveraged.[Results] The landslide body is in a continuous movement state,with a maximum cumulative deformation of ?20 mm and an annual average deformation rate of -8 mm·a?1.Based on airborne LiDAR data,three main landslide cracks at the rear and front edges of the landslide,as well as two engineering deformation boundaries spatially coinciding with the existing anti -slide piles,are accurately identified.The spatial overlay analysis of deformation and cracks shows that the high deformation rate zone (deformation rate of [?8,?4.8) mm·a?1) highly coincides with the dense crack development zone;the main parts of two major cracks are both located in the high deformation rate zone (accounting for 66.7%),and the main part of one major crack is located in the medium deformation rate zone (deformation rate of [1.6,4.8) and [?4.8,?1.6) mm·a?1).The main parts of the two engineering deformation boundaries are both located in the high deformation rate zone (accounting for 100%),which reveals that the middle and front parts of the landslide are the critical areas for deformation accumulation and stress concentration.[Conclusions ] This landslide is a traction -type reactivated landslide triggered by anti -slide engineering failure and rainfall,and multi -source remote sensing collaborative technology can provide key technical support for the early identification,mechanism analysis,and risk prevention and control of landslide hazards.It also demonstrates that multi -source remote sensing collaboration can provide crucial technical support for early identification,mechanism analysis,and risk prevention and control of landslide hazards.

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李宁,陈青,桂敬聪,等.多源遥感揭示公路边坡变形与裂缝的耦合机制[J].长沙理工大学学报(自然科学版),2026,23(2):31-46.
LI Ning, CHEN Qing, GUI Jingcong, et al. Coupling mechanism of deformation and cracks in highway slopes revealed by multi -source remote sensing[J]. Journal of Changsha University of Science & Technology (Natural Science),2026,23(2):31-46.

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  • 收稿日期:2025-12-27
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  • 在线发布日期: 2026-06-17
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