基于Morlet小波技术的北京平原地面沉降周期性分析

doi:10.13278/j.cnki.jjuese.20160364

吉林大学学报(地球科学版) ›› 2018, Vol. 48 ›› Issue (3): 836-845.doi: 10.13278/j.cnki.jjuese.20160364

基于Morlet小波技术的北京平原地面沉降周期性分析

王洁^1,2,3, 宫辉力^1,2,3, 陈蓓蓓^1,2,3, 高明亮^1,2,3, 周超凡^1,2,3, 梁悦^1,2,3, 陈文锋^1,2,3

1. 三维信息获取与应用教育部重点实验室, 北京 100048;
2. 城市环境过程与数字模拟国家重点实验室培育基地, 北京 100048;
3. 首都师范大学资源环境与旅游学院, 北京 100048

收稿日期:2017-12-29 出版日期:2018-05-26 发布日期:2018-05-26
作者简介:王洁(1991-),女,硕士研究生,主要从事区域地面沉降方面的研究,E-mail:jiewang1028@126.com
基金资助:
国家自然科学基金项目（41130744，41171335，41401492）；国家重点基础研究发展计划（"973"计划）项目（2012CB723403）；北京市教育委员会科技计划面上项目（KM201510028012）

Periodical Analysis of Land Subsidence in Beijing Plain Based on Morlet Wavelet Technology

Wang Jie^1,2,3, Gong Huili^1,2,3, Chen Beibei^1,2,3, Gao Mingliang^1,2,3, Zhou Chaofan^1,2,3, Liang Yue^1,2,3, Chen Wenfeng^1,2,3

1. Key Lab of 3D Information Acquisition and Application, Ministry of Education, Beijing 100048, China;
2. State Key Laboratory Breeding Base of Process of Urban Environment and Digital Simulation, Beijing 100048, China;
3. School of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China

Received:2017-12-29 Online:2018-05-26 Published:2018-05-26
Supported by:
Supported by National Natural Science Foundation of China (41130744, 41171335, 41401492), National Key Basic Research Program ("973" Program) of China (2012CB723403) and General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China (KM201510028012)

摘要/Abstract

摘要： 北京市地面沉降自20世纪60年代发现以来一直呈快速发展的趋势。不均匀地面沉降导致建筑物开裂、地基下沉，损害地下管道工程等基础设施，威胁城市安全。为了研究地面沉降发展的特征，分析其演化趋势，本文选取2011—2014年的27景Radarsat-2数据，采用干涉点目标分析技术，获取该时段北京平原区地面沉降时序监测信息；在此基础上，结合Morlet小波分析方法，根据相干点密度差异选取4个典型地面沉降区，分析其地面沉降多尺度演变特征。结果表明：地面沉降速率在空间分布上存在差异性，最大沉降速率为162.70 mm/a，年均沉降速率50.08 mm/a；地面沉降在时间域具有明显的局部周期性变化特征。在28 T （1 T表示1个24 d的时间段）的时间尺度下，存在着约13.3月的时间周期，不同位置还存在不同的不稳定震荡周期。

关键词: 地面沉降, 干涉点目标分析, Morlet小波, 周期性

Abstract: Land subsidence in Beijing has been developing rapidly since it was discoverd in the 1960s. Uneven ground deformation can destory buildings, and urban infrastructures such as underground pipelines,threatening urban security. In order to analyze the characteristics and the evolution trend of land subsidence in Beijing plain, 27 scenes of Radarsat-2 data from 2011 to 2014 were collected, and the interference point target analysis (IPTA) technology was performed, to obtain the time series land subsidence information. On this basis, four land subsidence areas were selected representatively, and multi-scale evolution characteristics of land subsidence were analyzed through Morlet wavelet tranform respectively. The results show that the maximum subsidence rate is 162.70 mm/a while the average rate is 50.08 mm/a, and subsidence rates are quite different among these areas in spatial distribution. Moreover, the wavelet transforms analysis indicates that the land subsidence present obvious local periodic variation characteristics in the time domain. In particular, at the time scale of 28 T(1 T represents a perod of 24 d), there is a time period of about 13.3 months, with different unstable oscillation periods in different positions.

Key words: land subsidence, interference point target analysis (IPTA), Morlet wavelet, periodicity

中图分类号:

P642.26

王洁, 宫辉力, 陈蓓蓓, 高明亮, 周超凡, 梁悦, 陈文锋. 基于Morlet小波技术的北京平原地面沉降周期性分析[J]. 吉林大学学报(地球科学版), 2018, 48(3): 836-845.

Wang Jie, Gong Huili, Chen Beibei, Gao Mingliang, Zhou Chaofan, Liang Yue, Chen Wenfeng. Periodical Analysis of Land Subsidence in Beijing Plain Based on Morlet Wavelet Technology[J]. Journal of Jilin University(Earth Science Edition), 2018, 48(3): 836-845.

参考文献

[1] 郑铣鑫,武强,侯艳声,等. 关于城市地面沉降研究的几个前沿问题[J].地球学报, 2002, 23(3):279-282. Zheng Xixin, Wu Qiang, Hou Yansheng, et al. Some Frontier Problems on Land Subsidence Research[J]. Acta Geoscientica Sinica, 2002, 23(3):279-282.
[2] 贾三满,王海刚,赵守生,等. 北京地面沉降机理研究初探[J].城市地质, 2007,2(1):20-26. Jia Sanman, Wang Haigang, Zhao Shousheng, et al. A Tentative Study of the Mechanism of Land Subsidence in Beijing[J]. City Geology, 2007,2(1):20-26.
[3] Galloway D L, Hudnut K W, Ingebritsen S E, et al. Detection of Aquifer System Compaction and Land Subsidence Using Interferometric Synthetic Aperture Radar, Antelope Valley, Mojave Desert, California[J]. Water Resources Research, 1998, 34(10):2573-2585.
[4] Ferretti A, Prati C, Rocca F. NonlinearSubsidence Rate Estimation Using Permanent Scatterers in Differential SAR Interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000,38(5):2201-2212.
[5] Werner C, Wegmuller U, Wiesmann A, et al. Inter-ferometric Point Target Analysis with JERS-1 L-Band SAR Data[C]//Geoscience and Remote Sensing Symposium. IGARSS'03 Proceedings. Toulouse:IEEE, 2003:4359-4361.
[6] 俞晓莹,姜成岭,张建,等. IPTA监测圣佩德罗湾港口地表时序沉降[J].测绘科学, 2012, 37(6):21-25. Yu Xiaoying, Jiang Chengling, Zhang Jian, et al. IPTA Monitoring Long-Term Series Surface Deformation of SAN PEDRO[J]. Science of Surveying & Mapping, 2012, 37(6):21-25.
[7] Zhang Yonghong, Zhang Jixian, Wu Hongan, et al. Monitoring of Urban Subsidence with SAR Interferometric Point Target Analysis:A Case Study in Suzhou, China[J]. International Journal of Applied Earth Observation & Geoinformation, 2011, 13(5):812-818.
[8] 张海波,李宗春,许兵,等. IPTA方法在地面沉降监测中的应用[J].测绘科学技术学报,2016, 33(2):145-149. Zhang Haibo, Li Zongchun, Xu Bing, et al. Ground Subsidence Monitoring Using Interferometric Point Target Analysis[J]. Journal of Geomatics Science and Technology, 2016, 33(2):145-149.
[9] 张雯,宫辉力,陈蓓蓓,等. 北京典型区地面沉降演化特征与成因分析[J].地球信息科学学报, 2015, 17(8):909-916. Zhang Wen, Gong Huili, Chen Beibei, et al. Evolution and Genetic Analysis of Land Subsidence in Beijing Typical Area[J]. Journal of Geo-Information Science, 2015, 17(8):909-916.
[10] 杨艳,贾三满,王海刚.北京平原区地面沉降现状及发展趋势分析[J].上海地质,2010(4):23-28. Yang Yan, Jia Sanman, Wang Haigang. The Status and Development of Land Subsidence in Beijing Plain[J]. Shanghai Geology, 2010(4):23-28.
[11] 葛大庆,殷跃平,王艳,等. 地面沉降-回弹及地下水位波动的InSAR长时间序列监测:以德州市为例[J].国土资源遥感,2014,26(1):103-109. Ge Daqing, Yin Yueping, Wang Yan, et al. Seasonal Subsidence-Rebound and Ground Water Level Changes Monitoring by Using Coherent Target Insar Technique:A Case Study of Dezhou,Shandong[J]. Remote Sensing for Land & Resources, 2014, 26(1):103-109.
[12] 雷坤超,陈蓓蓓,贾三满,等. 基于PS-InSAR技术的北京地面沉降特征及成因初探[J]. 光谱学与光谱分析, 2014,34(8):2185-2189. Lei Kunchao, Chen Beibei, Jia Sanman, et al. Primary Investigation of Formation and Genetic Mechanism of Land Subsidence Based on PS-InSAR Technology in Beijing[J]. Spectroscopy and Spectral Analysis, 2014, 34(8):2185-2189.
[13] Chai Jinchun, Shen Shuilong, Zhu Hehua, et al. Land Subsidence Due to Droundwater Drawdown in Shanghai[J]. Géotechnique, 2004, 54(2):143-147.
[14] Amelung F, Galloway D L, Bell J W, et al. Sensing the Ups and Downs of Las Vegas:InSAR Reveals Structural Control of Land Subsidence and Aquifer-System Deformation[J]. Geology, 1999, 27(6):483-486.
[15] Chaussard E, Amelung F, Abidin H, et al.Sinking Cities in Indonesia:ALOS PALSAR Detects Rapid Subsidence due to Groundwater and Gas Extraction[J].Remote Sensing of Environment,2013, 128(1):150-161.
[16] 陈蓓蓓,宫辉力,李小娟,等. PS-InSAR技术与多光谱遥感建筑指数的载荷密度对地面沉降影响的研究[J]. 光谱学与光谱分析, 2013, 33(8):2198-2202. Chen Beibei, Gong Huili, Li Xiaojuan, et al. The Impact of Load Density Differences on Land Subsidence Based on Build -Up Index and PS -InSAR Technology[J]. Spectroscopy and Spectral Analysis, 2013, 33(8):2198-2202.
[17] 付延玲, 骆祖江, 廖翔,等. 高层建筑引发地面沉降模拟预测三维流固全耦合模型[J]. 吉林大学学报(地球科学版), 2016,46(6):1781-1789. Fu Yanling, Luo Zujiang, Liao Xiang, et al. A Three-Dimensional Full Coupling Model to Simulate and Predict Land Subsidence Caused by High-Rise Building. Journal of Jilin University(Earth Science Edition), 2016, 46(6):1781-1789.
[18] 周超凡, 宫辉力, 陈蓓蓓,等. 利用数据场模型评价北京地面沉降交通载荷程度[J]. 吉林大学学报(地球科学版), 2017,47(5):1511-1520. Zhou Chaofan, Gong Huili, Chen Beibei, et al. Assessment to Ground Subsidence Traffic Load in Beijing Area Using Data Field Mode[J]. Journal of Jilin University(Earth Science Edition), 2017, 47(5):1511-1520.
[19] 王文圣,丁晶,向红莲.水文时间序列多时间尺度分析的小波变换法[J].四川大学学报(工程科学版),2002, 34(6):14-17. Wang Wensheng, Ding Jing, Xiang Honglian. Multiple Time Scales Analysis of Hydrological Time Series With Wavelet Transform[J]. Journal of Sichuan University(Engineering Science Edition), 2002, 34(6):14-17.
[20] 王文圣,丁晶,向红莲. 小波分析在水文学中的应用研究及展望[J]. 水科学进展, 2002,13(4):515-520. Wang Wensheng, Ding Jing, Xiang Honglian. Application and Prospect of Wavelet Analysis in Hydrology[J]. Advances in Water Science, 2002,13(4):515-520.
[21] 郭琳,宫辉力,朱锋,等. 基于小波分析的地下水水位与降水的周期性特征研究[J].地理与地理信息科学,2014,30(2):35-38. Guo Lin, Gong Huili, Zhu Feng, et al. Cyclical Characteristics of Groundwater Level and Precipitation Based on Wavelet Analysis[J]. Geography and Geo-Information Science, 2014,30(2):35-38.
[22] 倪夏梅,陈元芳,刘勇,等. 基于小波分析的枯水径流多时间尺度分析[J].水电能源科学, 2010, 28(3):6-8. Ni Xiamei, Chen Yuanfang, Liu Yong, et al. Multiple Time Scale Analysis of the Low Water Runoff Based on Wavelet Analysis[J]. Water Resources & Power, 2010, 28(3):6-8.
[23] Grinsted A, Moore J C, Jevrejeva S. Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series[J]. Nonlinear Processes in Geophysics, 2004, 11(5/6):561-566.
[24] 朱锋,宫辉力,李小娟,等. 基于InSAR和小波变换的不均匀沉降段识别:以京津高铁北京段为例[J].地理与地理信息科学, 2014, 30(1):23-27. Zhu Feng, Gong Huili, Li Xiaojuan, et al. Identification of Uneven Land Subsidence Segment Based on the InSAR and Wavelet Transformation:A Case Study of Beijing Section of Beijing-Tianjin High-Speed Railway[J]. Geography and Geo-Information Science, 2014, 30(1):23-27.
[25] Gao Mingliang, Gong Huili, Chen Beibei, et al. In SAR Time-Series Investigation of Long-Term Ground Displacement at Beijing Capital International Airport, China[J]. Tectonophysics, 2016, 691:271-281.
[26] 姜媛, 杨艳, 王海刚,等. 北京平原区地面沉降的控制与影响因素[J].上海国土资源, 2014,35(4):130-133. Jiang yuan, Yang Yan, Wang Haigang, et al. Factors Controlling Land Subsidence on the Beijing Plain[J]. Shanghai Land & Resources,2014,35(4):130-133.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

基于Morlet小波技术的北京平原地面沉降周期性分析

Periodical Analysis of Land Subsidence in Beijing Plain Based on Morlet Wavelet Technology

PDF (PC)

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 10

Metrics

本文评价

推荐阅读 0

[1]	周超凡, 宫辉力, 陈蓓蓓, 贾煦, 朱锋, 郭琳. 利用数据场模型评价北京地面沉降交通载荷程度[J]. 吉林大学学报(地球科学版), 2017, 47(5): 1511-1520.
[2]	付延玲, 骆祖江, 廖翔, 张建忙. 高层建筑引发地面沉降模拟预测三维流固全耦合模型[J]. 吉林大学学报(地球科学版), 2016, 46(6): 1781-1789.
[3]	秦喜文, 刘媛媛, 王新民, 董小刚, 张瑜, 周红梅. 基于整体经验模态分解和支持向量回归的北京市PM2.5预测[J]. 吉林大学学报(地球科学版), 2016, 46(2): 563-568.
[4]	付延玲，金玮泽，陈兴贤，谈金忠. 高层建筑荷载引发地面沉降与隆起变形三维数值模拟[J]. 吉林大学学报(地球科学版), 2014, 44(5): 1587-1594.
[5]	陈荣波，束龙仓，鲁程鹏，李伟. 含水层压密引起其特征参数变化的实验[J]. 吉林大学学报(地球科学版), 2013, 43(6): 1958-1965.
[6]	李文运, 崔亚莉, 苏晨, 张伟, 邵景力. 天津市地下水流-地面沉降耦合模型[J]. J4, 2012, 42(3): 805-813.
[7]	付延玲. 基于地面沉降控制的区域性松散沉积层地下水可采资源规划评价[J]. J4, 2012, 42(2): 476-484.
[8]	卢文喜, 陈社明, 王晨子, 刘磊, 贾洪玮, 吕德全. 基于小波变换的大安地区年降水量变化特征[J]. J4, 2010, 40(1): 121-127.
[9]	骆祖江, 曾峰, 李颖. 地下水开采与地面沉降控制三维全耦合模型研究[J]. J4, 2009, 39(6): 1080-1088.
[10]	于军，苏小四，朱琳，段福洲，高立，吴曙亮. 苏锡常地区地面沉降地质结构三维可视化模型虚拟现实系统研究[J]. J4, 2007, 37(2): 393-399.