城市目标动态监测中的时序InSAR分析方法及应用

廖明生; 王茹; 杨梦诗; 王楠; 秦晓琼; 杨天亮

doi:10.12000/JR20022

城市目标动态监测中的时序InSAR分析方法及应用

DOI: 10.12000/JR20022

廖明生^1, ,,
王茹^1,,
杨梦诗^1, ,,
王楠^1,,
秦晓琼^2,,
杨天亮³

1.
武汉大学测绘遥感信息工程国家重点实验室武汉 430079
2.
深圳大学建筑与城市规划学院深圳 518060
3.
上海市地质调查研究院上海 200072

基金项目: 国家重点研发计划课题(2019YFC1509200)，国家自然科学基金(41571435)，中国博士后科学基金(2019M660210)

详细信息

作者简介:
廖明生(1962–)，男，武汉大学教授，博士生导师，珞珈杰出学者。主要从事航空航天遥感影像信息处理的理论与方法的研究。E-mail: liao@whu.edu.cn

王　茹(1994–)，女，武汉大学博士生。主要研究方向为时间序列合成孔径雷达干涉测量技术及其应用分析。E-mail: wangr2017@whu.edu.cn

杨梦诗(1990–)，女，武汉大学博士生。主要研究方向为合成孔径雷达干涉测量技术与应用。E-mail: yangms@whu.edu.cn

王　楠(1993–)，女，山西忻州人，武汉大学测绘遥感信息工程国家重点实验室博士生。主要研究方向为时间序列InSAR分析及变形监测。E-mail: wangnannan@whu.edu.cn

秦晓琼(1991–)，女，博士，深圳大学助理研究员。主要研究方向为雷达干涉测量地表形变监测与反演。E-mail: xqqin@szu.edu.cn

杨天亮(1979–)，男，工学博士，正高级工程师，现任上海市地质调查研究院地面沉降研究所所长，兼任自然资源部地面沉降监测与防治重点实验室副主任。主要从事城市地质及地面沉降防治应用研究

通讯作者:
廖明生 liao@whu.edu.cn

杨梦诗 yangms@whu.edu.cn

责任主编：张红 Corresponding Editor: ZHANG Hong
中图分类号: TN959.3
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出版历程
- 收稿日期: 2020-03-21
- 修回日期: 2020-06-04
- 网络出版日期: 2020-06-01

Techniques and Applications of Spaceborne Time-series InSAR in Urban Dynamic Monitoring

1.
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2.
School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
3.
Shanghai Institute of Geological Survey, Shanghai 200072, China

Funds: The National Key Research and Development Program of China (2019YFC1509200), The National Natural Science Foundation of China (41571435), The National Science Foundation for Post-doctoral Scientists of China (2019M660210)

More Information

Corresponding author: LIAO Mingsheng, liao@whu.edu.cn; YANG Mengshi, yangms@whu.edu.cn

摘要

摘要: 城市地表和人工建筑的稳定性监测一直是城市安全的重要监测内容之一。星载合成孔径雷达干涉测量(InSAR)技术以其大范围、高精度、高空间密度的形变获取能力，被广泛用于大范围地表形变监测。近年来，随着星载SAR系统分辨率的不断提高，时序InSAR技术越来越多地应用于重要基础设施的监测。该文结合作者团队长期基于时序InSAR技术在城市地区监测研究经历，总结和回顾了团队关于时序InSAR方法在城市动态监测中的一些典型应用，包括城市机场、高架路网、桥梁、铁路和地铁沿线等，根据多年获取的高分辨率TerraSAR-X影像、Cosmo-SkyMed影像以及后续免费获取的Sentinel-1影像等多种数据以及监测研究中发现的研究问题及相应解决方法，在应用中取得了良好的效果，展现了时序InSAR技术在城区目标精细监测中的潜力。
- 雷达干涉测量 /
- 时间序列InSAR分析 /
- 形变监测 /
- 城市目标识别 /
- 人工建筑物监测 /
- 地表沉降
Abstract: The dynamic monitoring of the geological environment in urban areas, including the monitoring of the urban surface stability and detailed monitoring of man-made objects on the surface, is very important for ensuring effective and safe urban development. Spaceborne time-series InSAR technology is widely used to monitor urban deformation due to its large scale, high accuracy, and ability to acquire high-density spatial deformations. In recent years, with the operation of high-resolution satellite missions, time-series InSAR has also been widely used to monitor infrastructures. In this paper based on our long-term monitoring research experience in urban areas using the time-series InSAR technique, we review the application of some typical time-series-InSAR cases to the urban environment, including the monitoring of urban surface displacement and typical large infrastructures, including the airports, elevated road networks, bridges, railways, and subways. Based on various datasets including high-resolution TerraSAR-X images, Cosmo-SkyMed images, and recent Sentinel-1 images obtained at no cost, and the research problems and corresponding solutions identified in published monitoring research, we found good results to have been achieved using this application. With the implementation of more and more satellite missions, this technology will provide more possibilities for urban monitoring.
- SAR interferometry /
- Time series InSAR technique /
- Deformation monitoring /
- Urban target recognition /
- Infrastructures monitoring /
- Land subsidence

HTML全文

图 1 星载雷达遥感与城市动态监测应用的研究进展

Figure 1. Research progress of spaceborne time-series InSAR technique in urban dynamic monitoring

下载: 全尺寸图片幻灯片

图 2 上海地区及浦东机场2013.4—2019.3沉降速率分布图

Figure 2. Deformation velocity map in Shanghai and Pudong Airport from April 2013 to March 2019

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图 3 相干点沉降时间序列图

Figure 3. Deformation time-series of coherent points by time series InSAR

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图 4 水准点和时间序列InSAR相干点沉降速率对比图

Figure 4. Comparison of deformation velocity between leveling points and coherent points by time series InSAR

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图 5 武汉市2015.4—2017.7地表形变速率场

Figure 5. Deformation velocity map in Wuhan from April 2015 to July 2017

下载: 全尺寸图片幻灯片

图 6 城市环境下人工地物与微波信号之间的几种交互作用类型示意图

Figure 6. Sketch of several types of interaction between man-made objects and microwave signals in urban areas

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图 7 上海浦东国际机场历年年度沉降速率分布图

Figure 7. Annual settlement rate of Shanghai Pudong International Airport

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图 8 上海高架路历年年度沉降速率分布图

Figure 8. Annual settlement rate of elevated roads in Shanghai

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图 9 卢浦大桥形变速率分布图

Figure 9. Deformation velocity of Lupu bridge

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图 10 卢浦大桥

Figure 10. Lupu Bridge

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图 11 不同数据集卢浦大桥沉降剖面的交叉验证

Figure 11. Cross-validation of the settlement profile of Lupu Bridge from different datasets

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图 12 京津城际高铁2008.2—2009.12期间形变图

Figure 12. Deformation of the Beijing-Tianjin railway from February 2008 to December 2009

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图 13 京津城际高铁沿线缓冲区200.2—2009.12期间形变图

Figure 13. Subsidence rate of the buffer zone along the Beijing-Tianjin railway from February 2008 to December 2009

下载: 全尺寸图片幻灯片

图 14 京津城际高铁沿线灾害风险等级评估

Figure 14. Hazardous grading of Beijing-Tianjin railway

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图 15 2015.4—2017.7武汉市地铁线路和区域沉降对比示意图

Figure 15. Comparison of subway lines and regional deformation in Wuhan from April 2015 to July 2017

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图 16 武汉市地铁沿线2015.4—2017.7沉降速率梯度图

Figure 16. Deformation velocity gradient along the subway in Wuhan from April 2015 to July 2017

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表 1 2013.9—2018.9高架道路沉降情况对比

Table 1. Comparison of the deformation of elevated roads during from September 2013 to September 2018

年份	沉降速率范围(mm/yr)	沉降相干点百分比(%)	沉降点平均速率(mm/yr)	回弹点平均速率(mm/yr)
2013.9—2014.10	–14～8	55.46	–2.651	1.028
2014.9—2015.10	–15～11	46.31	–2.433	0.928
2015.9—2016.10	–14～10	39.54	–1.953	1.039
2016.10—2017.10	–10～10	49.97	–2.932	2.602
2017.9—2018.9	–10～10	29.00	–2.164	2.548

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