南京大学学报(自然科学版) ›› 2019, Vol. 55 ›› Issue (3): 370–380.doi: 10.13232/j.cnki.jnju.2019.03.004

所属专题: 测试专题

• 地面沉降 • 上一篇    下一篇

基于时序InSAR的常州市2015-2018年地面沉降监测

董少春*,种亚辉,胡 欢,黄璐璐   

  1. 南京大学地球科学与工程学院,南京,210023
  • 收稿日期:2019-02-03 出版日期:2019-06-01 发布日期:2019-05-31
  • 通讯作者: 董少春 E-mail:dsc@nju.edu.cn
  • 基金资助:
    国家自然科学基金(41372353)

Ground subsidence monitoring during 2015-2018 in Changzhou based on time series InSAR method

Dong Shaochun*,Chong Yahui,Hu Huan,Huang Lulu   

  1. School of Earth Sciences and Engineering,Nanjing University,Nanjing,210023,China
  • Received:2019-02-03 Online:2019-06-01 Published:2019-05-31
  • Contact: Dong Shaochun E-mail:dsc@nju.edu.cn

摘要: 地面沉降不仅会对城市公共基础设施造成安全隐患,也会对当地的经济、环境和可持续发展造成影响. 常州市位于我国著名的苏锡常地面沉降带,也是长三角地区的重要城市之一. 地面沉降监测一直是该地区掌握地面沉降状态、预防地面沉降灾害的重要举措. 利用2015年5月至2018年5月期间的36景Sentinel-1A的IW(Interferometric Wide Swath)模式的SLC(Single Look Complex) SAR(Synthetic Aperture Radar)数据,基于时序InSAR(Interferometric Synthetic Aperture Radar)方法对常州市地面沉降进行了监测,获得了常州地区该时间段年均沉降速率和时序地表累计形变图,揭示了观测期间常州市各地区详细的地面沉降时空分布和变化特征. 结果表明,在2015-2018年整个观测期间,常州地区地表形变呈现出“整体相对稳定,武进区局部沉降和抬升较为突出”的特征,与该地区历史沉降监测结果具有良好的一致性和延续性. 这一监测结果有助于全面掌握常州地区最近的地面沉降状况,建立并完善长期、连续的地面沉降时空演化监测记录,为城市基础设施选址、规划以及建立预警预报机制等提供决策依据.

关键词: 地面沉降, 干涉差分, 时序分析, 小基线集方法, 常 州

Abstract: Ground subsidence can cause damage to urban infrastructure,and thread adverse impacts on local ecnomic,environment and sustainable development. Changzhou is located in“Su-Xi-Chang”land subsidence zone in China,and is one of the most developed cities in Yangzi delta zone. Ground subsidence monitoring has been an important measure to understand the situation of ground subsidence and mitigate its damage. In order to fully understand the spatial-temporal distribution and feature of ground subsidence in Changzhou,we adopted SBAS(Small Baseline Subset) InSAR(Interferometric Synthetic Aperture Radar) method to 36 SLC(Single Look Complex) SAR(Synthetic Aperture Radar) data acquired by Sentinel 1A in IW(Interferometric Wide Swath) mode from 2015-2018. The LOS(Line of Sight) linear deformation rate map was generated and time-series of ground deformation were derived. The results show that most of the research area remains comparatively stable during the observation period,except for some areas in Wujin district,where obviously ground subsidence and uplift were detected. Detailed spatial-temporal ground subsidence analysis was analyzed in different district of Changzhou city. This result shows coincident with previous monitoring results and helps to fully understand the spatial-temporal characteristics of ground subsidence in the research area. It also helps to establish continuous monitoring records and provides valuable information for site selection and planning for new urban constructions,establishing early warning systems and forecasting mechanism for urban gound subsidence hazards.

Key words: ground subsidence, differential interferometry, time series analysis, SBAS(Small Baseline Subset) method, Changzhou

中图分类号: 

  • P237
[1] 薛禹群,张 云,叶淑君等. 我国地面沉降若干问题研究. 高校地质学报,2006,12(2):153-160.(Xue Y Q,Zhang Y,Ye S J,et al. Research on the problems of land subsidence in China. Geological Journal of China Universities,2006,12(2):153-160.)
[2] 夏 雄,董亮亮,张爱琴等. 常州区域地面沉降变化规律研究. 常州大学学报(自然科学版),2012,24(2):45-48.(Xia X,Dong L L,Zhang A Q,et al. Research on variation of land subsidence in Changzhou. Journal of Changzhou University(Natural Science Edition),2012,24(2):45-48.)
[3] 张 蓉. 常州市地面沉降分析及对策探讨. 江苏水利,2004,11:36-37.(Zhang R. Analysis and discussion on surface subsidence and measures in Changzhou. Jiangsu Water Resource,2004,11:36-37.)
[4] 王光亚,于 军,吴曙亮等. 常州地区地面沉降及地层压缩性研究. 地质与勘探,2009,45(5):612-620.(Wang G Y,Yu J,Wu S L,et al,Land subsidence and compression of soil layers in Changzhou area. Geology and Exploration,2009,45(5):612-620.)
[5] 朱兴贤. 常州市地面沉降灰色模型预测. 水文地质工程地质,1992,19(2):47-48.
[6] 于 军,王晓梅,武健强等. 苏锡常地区地面沉降特征及其防治建议. 高校地质学报,2006,12(2):179-184.(Yu J,Wang X M,Wu J Q,et al. Characteristics of land subsidence and its remedial proposal in Suzhou-Wuxi-Changzhou area. Geological Journal of China Universities,2006,12(2):179-184.)
[7] 佘孟信. 苏锡常地区地面沉降现状和治理对策研究. 地下水,1994,16(4):178-181.
[8] 薛禹群,吴吉春,张 云等. 长江三角洲(南部)区域地面沉降模拟研究. 中国科学 D辑:地球科学,2008,38(4):477-492.(Xue Y Q,Wu J C,Zhang Y,et al. Simulation of regional land subsidence in the southern Yangtze Delta. Science in China Series D:Earth Sciences,2008,51(6):808-825.)
[9] 薛禹群,张 云. 长江三角洲南部地面沉降与地裂缝. 华东地质,2016,37(1):1-9.(Xue Y Q,Zhang Y,Land subsidence and land fissures in the southern Yangtze river delta. East China Geology,2016,37(1):1-9.)
[10] 徐丹青,郭春香. 常州市区地面沉降分析及防治. 能源技术与管理2006(6):46-47.
[11] 袁修锦,钱 静. 常州市地质环境保护措施及展望. 地下水,2013,35(1):109-111.
[12] 于 军,李振洪,武健强. InSAR/GPS集成技术在常州-无锡地面沉降监测中的应用研究. 自然科学进展,2009,19(11):1267-1271.
[13] 丁荣荣,徐 佳,林晓彬等. 基于PSInSAR技术的常州地表形变监测研究. 测绘与空间地理信息,2015,38(2):51-54.(Ding R R,Xu J,Lin X B. Changzhou monitoring surface subsidence using PSInSAR. Geomatics & Spatial Information Technology,2015,38(2):51-54.)
[14] 林 辉,柯长青. COSMO-SkyMed 数据在常州市地表形变监测中的应用. 遥感技术与应用,2016,31(3):599-606.(Lin H,Ke C. Monitoring surface deformation in Changzhou City unsing Cosmo-SkyMed data. Remote Sensing Technology and Application,2016,31(3):599-606.)
[15] 夏磊凯,付五洲,黄其欢. 永久散射体差分干涉测量和小基线集技术在常州地面沉降分析中的应用. 勘察科学技术,2016(6):46-49.(Xia L K,Fu W Z,Huang Q H. Application of PS-InSAR and SBAS technology in land subsidence monitoring analysing in Changzhou. Site Investigation Science and Technology,2016(6):46-49.)
[16] 刘 波,晏王波,范雪婷等. 基于SBAS技术的武进区地面沉降监测应用研究. 现代测绘,2016,39(4):9-12.(Liu B. Yan W B,Fan X T,et al. Study on the application for ground subsidence monitoring in Wujin district based on SBAS technology. Modern Surveying and Mapping,2016,39(4):9-12.)
[17] Massonnet D,Rossi M,Carmona C,et al. The displacement field of the Landers earthquake mapped by radar interferometry. Nature,1993,364(8):138-142.
[18] Dzurisin D,Lisowski M,Wicks C W,et al. Geodetic observations and modeling of magmatic inflation at the Three Sisters volcanic center,central Oregon Cascade Range,USA. Journal of Volcanology and Geothermal Research,2006,150(1-3):35-54.
[19] Casu F,Manzo M,Lanari R. A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from DInSAR data. Remote Sensing of Environment,2006,102(3-4):195-210.
[20] Lopez-Quiroz P,Doin M P,Tupin F,et al. Time series analysis of Mexico City subsidence constrained by radar interferometry. Journal of Applied Geophysics,2009,69(1):1-15.
[21] Ng A H M,Ge L,Yan Y,et al. Mapping accumulated mine subsidence using small stack of SAR differential interferograms in the Southern coalfield of New South Wales,Australia. Engineering Geology,2010,115(1-2):1-15.
[22] Jiang L M,Lin H,Ma J W,et al. Potential of smallbaseline SAR interferometry for monitoring land subsidence related to underground coal fires:Wuda(Northern China)case study. Remote Sensing of Environment,2011,115(2):257-268.
  [23] Samsonov S,d’Oreye N,Smets B. Ground deformation associated with post-mining activity at the French-German border revealed by novel InSAR time series method. International Journal of Earth Observation and Geoinformation,2013,23:142-154.
[24] Schmidt D A,Burgmann R. Time dependent land uplift and subsidence in the Santa Clara Valley,California,from a large interferometric synthetic aperture data set. Journal of Geophysical Research,2003,108(B9):2416.
[25] 葛大庆,王 艳,郭小方等. 基于相干点目标的多基线D-InSAR技术与地表形变监测. 遥感学报,2007,11(4):574-580.(Ge D Q,Wang Y,Guo X F,et al. Surface deformation monitoring with multi-baseline D-InSAR based on coherent point target. Journal of Remote Sensing,2007,11(4):574-580.)
[26] 范景辉,郭华东,郭小方等. 基于相干目标的干涉图叠加方法监测天津地区地面沉降. 遥感学报,2008,12(1):111-118.(Fan J H,Guo H D,Guo X F,et al. Monitoring subsidence in Tianjin area using interferogram stacking based on coherent targets. Journal of Remote Sensing,2008,12(1):111-118.)
[27] Gonzlez P J,Tiampo K F,Camacho A G,et al. Shallow flank deformation at Cumbre Vieja volcano(Canary Islands):Implications on the stability of steep-sided volcano flanks at oceanic islands. Earth and Planetary Science Letters,2010,297(3-4):545-557.
[28] Dong S C,Samsonov S,Yin H W,et al. Time-series analysis of subsidence associated with rapid urbanization in Shanghai,China measured with SBAS InSAR method. Environmental Earth Sciences,2014,(72):677-691.
[29] 李广宇,张 瑞,刘国祥等. Sentinel-1A TS-DInSAR京津冀地区沉降监测与分析. 遥感学报,2018,22(4):633-646.(Li G Y,Zhang R,Liu G X,et al. Land subsidence detection and analysis over Beijing-Tianjin-Hebei area based on Sentinel-1A TS-DInSAR. Journal of Remote Sensing,2018,22(4):633-646.)
[30] Ferretti A,Prati C,Rocca F. Permanent scatterers in SAR interferometry. IEEE Transaction on Geoscience and Remote Sensing,2001,39(1):8-20.
[31] Berardino P,Fornaro G,Lanari R,et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing,2002,40(11):2375-2383.
[32] Samsonov S,van der Kooij M,Tiampo K. A simultaneous inversion for deformation rates and topographic errors of DInSAR data utilizing linear least square inversion technique. Computer & Geosciences,2011,37(8):1083-1091.
[1] 杨 蕴, 宋 健, 朱 琳, 吴剑锋, 王锦国. 基于KELM地面沉降替代模型的地下水多目标管理模型研究[J]. 南京大学学报(自然科学版), 2019, 55(3): 349-360.
[2] 曹 群,陈蓓蓓,宫辉力,周超凡,罗 勇,高明亮,王 旭,史 珉,赵笑笑,左俊杰. 基于SBAS和IPTA技术的京津冀地区地面沉降监测[J]. 南京大学学报(自然科学版), 2019, 55(3): 381-391.
[3] 吕海敏,沈水龙,严学新,史玉金,许烨霜. 上海地面沉降对轨道交通安全运营风险评估[J]. 南京大学学报(自然科学版), 2019, 55(3): 392-400.
[4] 徐成华,谈金忠,骆祖江,李 兆. 地铁盾构施工引发地面沉降三维流固全耦合数值模拟预测[J]. 南京大学学报(自然科学版), 2019, 55(3): 409-419.
[5] 叶 超,田 芳,罗 勇,王新惠,田苗壮,崔文君,王立发,雷坤超. 北京地面沉降控制区划及防控措施[J]. 南京大学学报(自然科学版), 2019, 55(3): 440-448.
[6] 严学新,杨天亮,林金鑫,黄鑫磊,王建秀. 超深基坑减压降水引发地面沉降的估算及其影响因素分析[J]. 南京大学学报(自然科学版), 2019, 55(3): 401-408.
[7] 杨建民,于佳卉,霍王文. 区域性地面沉降形状参数c1与c2间线性关系研究[J]. 南京大学学报(自然科学版), 2019, 55(3): 420-428.
[8] 毛 磊,张 岩,刘明遥,龚绪龙,于 军,叶淑君. 江苏沿海地区地面沉降约束下的地下水可采资源量评价[J]. 南京大学学报(自然科学版), 2019, 55(3): 429-439.
[9] 罗 跃,严学新,杨天亮,叶淑君,吴吉春. 上海陆域地区地下水采灌与地面沉降的时空特征[J]. 南京大学学报(自然科学版), 2019, 55(3): 449-457.
[10] 卢 毅,于 军,龚绪龙,王宝军,魏广庆,季峻峰. 基于DFOS的连云港第四纪地层地面沉降监测分析[J]. 南京大学学报(自然科学版), 2018, 54(6): 1114-1123.
[11]  杨 蕴1,朱 琳2*,林 锦3,王锦国1.  考虑地面沉降约束的地下水模拟优化管理模型[J]. 南京大学学报(自然科学版), 2016, 52(3): 470-478.
[12] 贺小桐1,叶淑君1*,于军2,吴吉春1,龚绪龙2. 基于固体颗粒速度场的三维地面沉降模拟[J]. 南京大学学报(自然科学版), 2015, 51(6): 1268-1278.
[13]  叶淑君 1 ** , 薛禹群 1 , 吴吉春 1 , 李勤奋 2 .  基于修正麦钦特模型的地面沉降模拟:以上海为例*

[J]. 南京大学学报(自然科学版), 2011, 47(3): 291-298.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 孙 玫,张 森,聂培尧,聂秀山. 基于朴素贝叶斯的网络查询日志session划分方法研究[J]. 南京大学学报(自然科学版), 2018, 54(6): 1132 -1140 .
[2] 周星星,张海平,吉根林. 具有时空特性的区域移动模式挖掘算法[J]. 南京大学学报(自然科学版), 2018, 54(6): 1171 -1182 .
[3] 韩明鸣, 郭虎升, 王文剑. 面向非平衡多分类问题的二次合成QSMOTE方法[J]. 南京大学学报(自然科学版), 2019, 55(1): 1 -13 .
[4] 刘 素, 刘惊雷. 基于特征选择的CP-nets结构学习[J]. 南京大学学报(自然科学版), 2019, 55(1): 14 -28 .
[5] 王伯伟, 聂秀山, 马林元, 尹义龙. 基于语义相似度的无监督图像哈希方法[J]. 南京大学学报(自然科学版), 2019, 55(1): 41 -48 .
[6] 孔 颉, 孙权森, 纪则轩, 刘亚洲. 基于仿射不变离散哈希的遥感图像快速目标检测新方法[J]. 南京大学学报(自然科学版), 2019, 55(1): 49 -60 .
[7] 贾海宁, 王士同. 面向重尾噪声的模糊规则模型[J]. 南京大学学报(自然科学版), 2019, 55(1): 61 -72 .
[8] 严云洋, 瞿学新, 朱全银, 李 翔, 赵 阳. 基于离群点检测的分类结果置信度的度量方法[J]. 南京大学学报(自然科学版), 2019, 55(1): 102 -109 .
[9] 阚 威, 李 云. 基于LSTM的脑电情绪识别模型[J]. 南京大学学报(自然科学版), 2019, 55(1): 110 -116 .
[10] 汪贵庆, 袁杰, 沈庆宏. 基于精英蚁群算法的交通最优路径研究[J]. 南京大学学报(自然科学版), 2019, 55(5): 709 -717 .