Journal of Jilin University(Earth Science Edition) ›› 2018, Vol. 48 ›› Issue (3): 836-845.doi: 10.13278/j.cnki.jjuese.20160364

Previous Articles     Next Articles

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

Wang Jie1,2,3, Gong Huili1,2,3, Chen Beibei1,2,3, Gao Mingliang1,2,3, Zhou Chaofan1,2,3, Liang Yue1,2,3, Chen Wenfeng1,2,3   

  1. 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)

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

CLC Number: 

  • P642.26
[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.
[1] Zhou Chaofan, Gong Huili, Chen Beibei, Jia Xu, Zhu Feng, Guo Lin. 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.
[2] Fu Yanling, Luo Zujiang, Liao Xiang, Zhang Jianmang. A Three-Dimensional Full Coupling Model to Simulate and Predict Land Subsidence Caused by High-Rise Building [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(6): 1781-1789.
[3] Qin Xiwen, Liu Yuanyuan, Wang Xinmin, Dong Xiaogang, Zhang Yu, Zhou Hongmei. PM2.5 Prediction of Beijing City Based on Ensemble Empirical Mode Decomposition and Support Vector Regression [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(2): 563-568.
[4] Fu Yanling,Jin Weize,Chen Xingxian,Tan Jinzhong. Three-Dimensional Numerical Simulation of Land Subsidence and Upheaval Deformation Caused by High-Rise Building Load [J]. Journal of Jilin University(Earth Science Edition), 2014, 44(5): 1587-1594.
[5] Chen Rongbo,Shu Longcang,Lu Chengpeng,Li Wei. Experimental Study on the Characteristic Parameters Variation of the Aquifer Caused by Aquifer Compaction [J]. Journal of Jilin University(Earth Science Edition), 2013, 43(6): 1958-1965.
[6] FU Yan-ling. Plan and Evaluation of Groundwater Exploitable Resources on the Basis of Land Subsidence Control in the Regional Loose Sediment Area [J]. J4, 2012, 42(2): 476-484.
[7] LEI Wen-xi, CHEN She-ming, WANG Chen-zi, LIU Lei, GU Hong-wei, LV De-quan. Variation Characteristics of Annual Precipitation in Da’an Area Based on Wavelet Transformation [J]. J4, 2010, 40(1): 121-127.
[8] YU Jun, SU Xiao-si, ZHU Lin, DUAN Fu-zhou, GAO Li, WU Shu-liang. Research on 3D Visualized Strata Model Virtual Reality System of Land Subsidence in Suzhou-Wuxi-Changzhou area [J]. J4, 2007, 37(2): 393-399.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!