光学与雷达遥感融合的铁路边坡三维形变监测与评价研究

张璇钰; 刘桂卫; 孙琪皓; 任光雪; 王飞; 王衍汇

doi:10.13238/j.issn.1004-2954.202409010003

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光学与雷达遥感融合的铁路边坡三维形变监测与评价研究

线路/路基/轨道 | 更新时间：2026-07-08

- 光学与雷达遥感融合的铁路边坡三维形变监测与评价研究
- Research on Three-Dimensional Deformation Monitoring and Evaluation of Railway Slopes by Integrating Optical and Radar Remote Sensing
- 铁道标准设计 2026年70卷第7期页码：41-47
- 作者机构：
  
  中国铁路设计集团有限公司，天津 300251
- 作者简介：
  
  作者简介：张璇钰（1995—），男，工程师，2021年毕业于西南交通大学测绘工程专业，工学硕士，主要从事铁路地质遥感技术研究工作，E-mail：434572780@qq. com。
- 基金信息：
  
  中国国家铁路集团有限公司科技开发计划重大课题(K2023G032);中国铁路设计集团有限公司科技开发重点课题(2023A0226408;2023A0226409)
- DOI：10.13238/j.issn.1004-2954.202409010003
  中图分类号： U213.1;P237
- 收稿：2024-09-01，
  
  修回：2024-10-14，
  
  网络首发：2025-04-30，
  
  纸质出版：2026-07-20
- 稿件说明：
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张璇钰, 刘桂卫, 孙琪皓, 等. 光学与雷达遥感融合的铁路边坡三维形变监测与评价研究[J]. 铁道标准设计, 2026,70(7):41-47.

ZHANG Xuanyu, LIU Guiwei, SUN Qihao, et al. Research on Three-Dimensional Deformation Monitoring and Evaluation of Railway Slopes by Integrating Optical and Radar Remote Sensing[J]. Railway Standard Design, 2026, 70(7): 41-47.
张璇钰, 刘桂卫, 孙琪皓, 等. 光学与雷达遥感融合的铁路边坡三维形变监测与评价研究[J]. 铁道标准设计, 2026,70(7):41-47. DOI： 10.13238/j.issn.1004-2954.202409010003.

ZHANG Xuanyu, LIU Guiwei, SUN Qihao, et al. Research on Three-Dimensional Deformation Monitoring and Evaluation of Railway Slopes by Integrating Optical and Radar Remote Sensing[J]. Railway Standard Design, 2026, 70(7): 41-47. DOI： 10.13238/j.issn.1004-2954.202409010003.

摘要

【

目的

】路堑边坡安全一直是铁路工程重点关注的问题。近年来，因路堑边坡变形破坏造成的工程事故屡有发生，对工程建设和运维安全构成巨大威胁。受山区地形起伏和植被覆盖等不利因素影响，传统人工调绘方法存在效率低、盲区多，且危险性高等问题；单点式形变监测方法难以获取边坡面域形变信息，易导致隐患的遗漏。为此，开展边坡三维形变监测与评价技术研究。【

方法

】以某在建铁路路堑边坡为研究对象，利用光学遥感像素偏移追踪和合成孔径雷达干涉（InSAR）方法，通过数据融合分析，明确边坡形变区的空间范围，并揭示其三维形变特征。【

结果

】基于光学遥感像素偏移追踪技术获取边坡二维平面形变，最大量级为84.71 mm；InSAR监测垂向形变与降水量呈正相关趋势，符合膨胀土遇水软化，失水干缩的特性；融合监测识别出一处潜在的小型～中型浅层滑坡体，滑体方量1.97×10

～4.54×10

。最大形变位于裂缝L1上游约35m处，形变方向为255°～270°，量级为85.59 mm；计算获得边坡降雨工况下稳定性系数为1.043，处于欠稳定状态，须开展工程治理。【

结论

】研究成果可为类似工程边坡监测提供参考。

Abstract

[

Objective

]

The safety of cutting slopes has always been a key concern in railway engineering. In recent years，engineering accidents caused by the deformation and failure of cutting slopes occur frequently，posing great threats to the safety of engineering construction and operation. Influenced by unfavorable factors such as undulating terrain and dense vegetation coverage in mountainous areas，traditional manual survey methods suffer from low efficiency，numerous blind spots，and high operational risks. Furthermore，single-point deformation monitoring methods are incapable of capturing surface-wide deformation information of slopes，which can easily lead to the omission of potential hazards. To this end，research on three-dimensional deformation monitoring and evaluation technology for slopes is conducted. [

Methods

]

A cutting slope of a railway under co

nstruction was taken as the research object. Optical remote sensing pixel offset tracking and synthetic aperture radar interferometry（InSAR）methods were employed，and data fusion analysis was conducted to delineate the spatial extent of the slope deformation zone and reveal its three-dimensional deformation characteristics. [

Results

]

Based on optical remote sensing pixel offset tracking technology，the two-dimensional planar deformation of the slope was obtained，with a maximum magnitude of 84. 71 mm. InSAR monitoring revealed a positive correlation between vertical deformation and precipitation，which was consistent with the characteristics of expansive soil—softening upon water absorption and shrinking upon desiccation. Fusion monitoring identified a potential small-to medium-sized shallow landslide，with a volume ranging from 1. 97×10

to 4. 54×10

. The maximum deformation was located approximately 35 m upstream of crack L1，with a deformation direction of 255°～270° and a magnitude of 85. 59 mm. The stability coefficient of the slope under rainfall conditions was calculated to be 1. 043，indicating a marginally unstable state requiring engineering treatment. [

Conclusion

]

The research findings can provide a reference for the monitoring of similar engineering slopes.

关键词

Keywords

references

张璇钰, 刘桂卫, 孙琪皓, 等.综合遥感技术在山区铁路泥石流勘察中的应用[J].铁道勘察, 2024, 50(1):16-22.

ZHANG Xuanyu, LIU Guiwei, SUN Qihao, et al. Application of Comprehensive Remote Sensing Technology in Mountain Railway Debris Flow Survey [J]. Railway Investigation and Surveying, 2024, 50(1):16-22.

张卢奔.基于无人机遥感和SAM的山区房屋提取研究[J].铁道勘察, 2024, 50(3):21-27.

ZHANG Luben. Research on the Extraction of House in Mountainous Area Based on UAV Remote Sensing and Segment anything Large Model [J]. Railway Investigation and Surveying, 2024, 50 (3):21-27.

许强, 陆会燕, 李为乐, 等.滑坡隐患类型与对应识别方法[J].武汉大学学报(信息科学版), 2022, 47(3):377-387.

XU Qiang, LU Huiyan, LI Weile, et al. Types of Potential Landslide and Corresponding Identification Technologies[J]. Geomatics and Information Science of Wuhan University, 2022, 47(3):377-387.

APU S I, SHARMILI N, GAZI M Y, et al. Remote Sensing and GIS-based Landslide Susceptibility Mapping in a Hilly District of Bangladesh: a Comparison of Different Geospatial Models[J]. Journal of the Indian Society of Remote Sensing, 2025, 53(2):531-548.

ZENG T X, ZHANG J, CHEN Y L, et al. Extraction of Spatiotemporal Information of Rainfall-induced Landslides from Remote Sensing [J]. Remote Sensing, 2024, 16(16):3089.

陈富强, 刘亚林, 高旭, 等.遥感技术在中尼铁路工程地质勘察中的应用[J].自然资源遥感, 2021, 33(4):219-226.

CHEN Fuqiang, LIU Yalin, GAO Xu, et al. Application of Remote Sensing Technology to the Engineering Geological Survey for the Construction of the China-Nepal Railway[J]. Remote Sensing for Natural Resources, 2021, 33(4):219-226.

刘桂卫, 李国和, 陈则连, 等.多源遥感技术在艰险山区铁路地质勘察中应用[J].铁道工程学报, 2019, 36(8):4-8.

LIU Guiwei, LI Guohe, CHEN Zelian, et al. Application of Remote Sensing Technology for Geological Investigation in Mountain Railways[J]. Journal of Railway Engineering Society, 2019, 36(8):4-8.

贾会会, 薛建志, 郭利召, 等.“空天地”一体化技术在采空区形变监测中的应用[J]. 中国地质灾害与防治学报, 2023, 34(3):69-82.

JIA Huihui, XUE Jianzhi, GUO Lizhao, et al. Application of Combined Space, Arial and Ground Based Multiple Technologies in Deformation Monitoring of Mining Areas[J]. The Chinese Journal of Geological Hazard and Control, 2023, 34(3):69-82.

QI W W, YANG W T, HE X L, et al. Detecting Chamoli Landslide Precursors in the Southern Himalayas Using Remote Sensing Data [J]. Landslides, 2021, 18(10):3449-3456.

柳林, 宋豪峰, 杜亚男, 等.联合哨兵2号和Landsat 8估计白格滑坡时序偏移量[J].武汉大学学报(信息科学版), 2021, 46(10):1461-1470.

LIU Lin, SONG Haofeng, DU Yanan, et al. Time-series Offset Tracking of the Baige Landslide Based on Sentinel-2 and Landsat 8[J]. Geomatics and Information Science of Wuhan University, 2021, 46(10):1461-1470.

SINGH JASROTIA A, AHMAD S, RIDWAN Q, et al. Estimation of Surface Ice Velocity of Durung Drung Glacier, Western Himalaya Using COSI-Corr from Landsat Images[J]. The Egyptian Journal of Remote Sensing and Space Sciences, 2024, 27(2):369-381.

叶江, 李才艺, 高红旗, 等.基于多时相光学遥感影像亚像素相关的边坡监测:以溪洛渡电站为例[J]. 测绘通报, 2024(1):38-43, 108.

YE Jiang, LI Caiyi, GAO Hongqi, et al. Sub-pixel Correlation-based Slope Monitoring Using Multi-temporal Optical Remote Sensing Images: a Case Study of Xiluodu Hydropower Station[J]. Bulletin of Surveying and Mapping, 2024(1):38-43, 108.

孔令昊.基于无人机摄影测量的边坡形变监测方法研究[D].武汉:武汉大学, 2023:2.

KONG Linghao. Research on Slope Deformation Monitoring Method Based on Drone Photogrammetry[D]. Wuhan: WuHan University, 2023:2.

杨治斌, 李刚, 毛燕婷, 等.不同偏移量追踪算法提取冰川流速的亚像素级精度比较[J].冰川冻土, 2024, 46(3):806-818.

YANG Zhibin, LI Gang, MAO Yanting, et al. Precision Comparison of Different Offset-tracking Methods at Sub-pixel Level for Glacier Velocity Study[J]. Journal of Glaciology and Geocryology, 2024, 46 (3):806-818.

董岳, 丁明涛, 李鑫泷, 等.基于光学遥感像素偏移量的金沙江流域2018年白格滑坡演变过程[J].地球科学与环境学报, 2022, 44(6):1002-1015.

DONG Yue, DING Mingtao, LI Xinlong, et al. Evolution of the 2018 Baige Landslides Revealed by Optical Remote Sensing Pixel Offsets in Jinsha River Basin, China[J]. Journal of Earth Sciences and Environment, 2022, 44(6):1002-1015.

刘卫南, 宋红克, 李清波, 等.利用光学影像的滑坡位移监测[J].测绘通报, 2024(6):41-45, 64.

LIU Weinan, SONG Hongke, LI Qingbo, et al. Landslide Displacement Monitoring Method by Optical Satellite Images[J]. Bulletin of Surveying and Mapping, 2024(6):41-45, 64.

朱建军, 胡俊, 李志伟, 等. InSAR滑坡监测研究进展[J].测绘学报, 2022, 51(10):2001-2019.

ZHU Jianjun, HU Jun, LI Zhiwei, et al. Recent Progress in Landslide Monitoring with InSAR[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(10):2001-2019.

逯中香, 樊彦国, 李国胜. 利用时序InSAR技术监测青藏铁路沿线地表形变[J].测绘通报, 2022(3):138-142, 156.

LU Zhongxiang, FAN Yanguo, LI Guosheng. Monitoring of Surface Deformation along the Qinghai-Tibet Railway with the Time Series In-SAR Technology[J]. Bulletin of Surveying and Mapping, 2022(3):138-142, 156.

刘晓杰.星载雷达遥感广域滑坡早期识别与监测预测关键技术研究[D].西安:长安大学, 2022:5.

Research on Key Technologies for Early Identification, Monitoring and Forecasting of Wide-area Landslides with Spaceborne Radar Remote Sensing[D]. Xi'an: Changan University, 2022:5.

盛磊.基于DS-InSAR技术的高山峡谷区滑坡三维形变提取及厚度反演[D].徐州:中国矿业大学, 2023:5-15.

SHENG Lei. Three-dimensional Deformation Extraction and Thickness Inversion of Landslides in Alpine and Canyon Region Based on DS-Insar Technology[D]. Xuzhou: China University of Mining and Technology, 2023:5-15.

李名语, 李政, 姚京川, 等.基于ISBAS-InSAR的京雄城际铁路建设期区域沉降监测及气候因子相关性分析[J].铁道学报, 2022, 44(11):71-81.

LI Mingyu, LI Zheng, YAO Jingchuan, et al. ISBAS-InSAR-based Ground Subsidence Monitoring and Climatic Correlation Analysis during Construction Period of Beijing—Xiongan Intercity Railway[J]. Journal of the China Railway Society, 2022, 44(11):71-81.

石固林, 陈强, 刘先文, 等.联合升降轨Sentinel-1A数据监测桃坪乡古滑坡沿坡向的形变速度场[J].工程地质学报, 2022, 30(4):1350-1361.

SHI Gulin, CHEN Qiang, LIU Xianwen, et al. Deformation Velocity Field along Aspect Direction of an Ancient Landslide at Taoping Village Derived from Ascending and Descending SENTINEL-1A Data [J]. Journal of Engineering Geology, 2022, 30(4):1350-1361.

余绍淮, 徐乔, 余飞.联合光学和SAR遥感影像的山区公路滑坡易发性评价方法[J].自然资源遥感, 2023, 35(4):81-89.

YU Shaohuai, XU Qiao, YU Fei. Method for Assessing Landslide Susceptibility of Highways in Mountainous Areas Based on Optical and SAR Remote Sensing Images[J]. Remote Sensing for Natural Resources, 2023, 35(4):81-89.

牛晶晶.融合星载SAR与无人机倾斜摄影测量数据的矿区地表形变监测方法[D].长沙:中南大学, 2023:11.

NIU Jingjing. Monitoring Surface Deformation of Mining Area by Fusing Satellite SAR and UAV Photogrammetry Data[D]. Changsha: Central South University, 2023:11.

赵颖.综合SAR和光学遥感影像的玛多地震同震及震后形变提取与分析[D].西安:长安大学, 2023:18-25.

ZHAO Ying. Extraction and Analysis of Maddow Earthquake Co-seismic and Post-Seismic Deformation Based on SAR and Optical Images [D]. Xi'an: Changan University, 2023:18-25.

ZAZI L, BENHAMOUDA F, GUETTOUCHE M S, et al. Exploring the Mila Landslide: Integrating Radar and Optical Remote Sensing for Enhanced Geohazard Assessment[C]//2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS ), Athens, National Observatory of Athens, 2024:129-133.

铁道部第一勘测设计院.铁路工程地质手册(修订版) [M]. 北京:中国铁道出版社, 2007.

国家质量监督检验检疫总局, 中国国家标准化管理委员会.滑坡防治工程勘查规范:GB/T 32864—2016[S].北京:中国标准出版社, 2017.

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