Please wait a minute...
img

官方微信

遥感技术与应用  2021, Vol. 36 Issue (6): 1358-1367    DOI: 10.11873/j.issn.1004-0323.2021.6.1358
遥感应用     
基于SBAS-InSAR技术的围填海区域地面沉降监测
林广坤(),吴志峰(),曹峥,关文川
广州大学 地理科学与遥感学院,广东 广州 510006
Land Subsidence Monitoring in Reclamation Area based on SBAS-InSAR Technique
Guangkun Lin(),Zhifeng Wu(),Zheng Cao,Wenchuan Guan
School of Geographic Science and Remote Sensing,Guangzhou University,Guangzhou 510006,China
 全文: PDF(6080 KB)   HTML
摘要:

以围填海活动为代表的沿海快速城市化过程,是引起地面沉降的重要影响因素之一。研究聚焦沿海围填海活动热点区域广州市南沙区,使用2015年6月~2018年4月共34景Sentinel-1数据,应用SBAS-InSAR技术,揭示了南沙区在研究时段内地面沉降的时空变化格局及演变特征。结果表明:①南沙区整体呈现持续沉降的趋势,沉降速率分化严重,平均沉降速率达到3.2 mm/a,圈层分析法显示中心圈层平均沉降速率为2.6 mm/a,最外层平均沉降速率为26.8 mm/a;②该区地面沉降在空间上呈现出异质性,主要分布在东部和南部,其中南部万顷沙、龙穴岛地面沉降最为严重,最大年沉降速率达到72.2 mm/a,在2015年6月~9月还出现地面沉降回弹现象,可能是台风天气带来季节性强降水变化影响。③基于不同极化方式的Sentinel-1数据进行交叉验证,VV极化、VH极化监测结果平均值分别为2.09 mm和1.01 mm,均方根误差分别为1.12 mm和2.65 mm。结果表明:SBAS-InSAR技术在提取围填海区域的地面沉降信息方面是有效可靠的,能更好地为监测沿海地区的地面沉降情况提供科学依据。

关键词: 围填海Sentinel?1SBAS?InSAR地面沉降时空演变    
Abstract:

The reclamation activities of rapid urbanization process is a significant factor to cause land subsidence. This study has focused on land subsidence along with the coastal reclamation activity over Nansha district in Guangzhou city. A total of 34 Synthetic Aperture Radar (SAR) images acquired by Sentinel1 between June 6, 2015 and April 2018 are used to monitor the surface deformation and find the spatial and temporal variations of land subsidence by employing a small baseline subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique. The results show that: (1) the Nansha district shows a trend of continuous subsidence of the whole.,but the land subsidence rate is highly polarization. The average settlement rate is 3.2 mm/a, while the center layer and the outermost layer are 2.6 mm/a and 26.8 mm/a, respectively;(2) The land subsidence shows spatial heterogeneity. The mainly distributed in the east and south, which Wanqingsha area and Longxue-Island in the south have the most serious land subsidence, with the maximum annual subsidence rate exceeding 60 mm/a (up to -68.9 mm/a). And the land subsidence rebound phenomenon also is found from June to September, 2015. (3) Cross-validation was conducted with different Sentinel-1 polarization modes. The average values of VV polarization and VH polarization monitoring results were 2.09 mm and 1.01 mm, respectively, and the root-mean-square errors are 1.12 mm and 2.65 mm, respectively. The results show that SBAS-InSAR technology is effective and reliable in extracting land subsidence information in the reclamation area and provides scientific basis for better monitoring land subsidence in coastal areas.

Key words: Reclamation    Sentinel-1    SBAS-InSAR    Land subsidence    Spatial and temporal variations
收稿日期: 2020-07-30 出版日期: 2022-01-26
ZTFLH:  P237  
基金资助: 国家自然科学基金重点项目“粤港澳大湾区湿地资源遥感监测及其生态功能评估研究项目”(U1901219)
通讯作者: 吴志峰     E-mail: zfwu@gzhu.edu.cn
作者简介: 林广坤(1995-),男,广东汕头人,硕士研究生,主要从事InSAR技术和地表形变监测。E?mail:zfwu@gzhu.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
林广坤
吴志峰
曹峥
关文川

引用本文:

林广坤,吴志峰,曹峥,关文川. 基于SBAS-InSAR技术的围填海区域地面沉降监测[J]. 遥感技术与应用, 2021, 36(6): 1358-1367.

Guangkun Lin,Zhifeng Wu,Zheng Cao,Wenchuan Guan. Land Subsidence Monitoring in Reclamation Area based on SBAS-InSAR Technique. Remote Sensing Technology and Application, 2021, 36(6): 1358-1367.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2021.6.1358        http://www.rsta.ac.cn/CN/Y2021/V36/I6/1358

图1  研究区位置示意图 审图号:粤S(2020)01-005
数据类型名称来源参数描述
SAR数据集Sentinel-1AESA轨道方向升轨
数据类型斜距单视复图像(SLC)
极化方式垂直发射垂直接收(VV); 垂直发射水平接收(VH)
成像方式干涉宽幅模式IW
分辨率方位向、距离向分别为20 m、5 m
DEMSRTMUSGS相对水平精度15 m
相对高程精度10 m
分辨率30 m×30 m
轨道定位数据PODESA定位精度优于5 cm
覆盖时间26 h
表1  研究数据说明表
编号日期

空间基线

/m

编号日期

空间基线

/m

02015-6-15-41172016-11-1219
12015-7-21-75182016-12-18-60
22015-8-2-39192017-1-1125
32015-9-7-98202017-2-2838
42015-9-19-58212017-3-12-14
52015-10-1-15222017-4-29-14
62016-1-17-34232017-5-11-67
72016-2-1052242017-6-28-31
82016-3-5-58252017-7-1025
92016-3-29-77262017-9-822
102016-5-40272017-10-2-43
112016-5-16-47282017-11-716
122016-6-9-26292017-12-159
132016-7-3-51302018-1-622
142016-8-20-35312018-1-3046
152016-9-13-33322018-2-11-28
162016-10-3115332018-4-24-27
表2  实验区SAR数据相关参数表
图2  SBAS-InSAR技术流程图
图3  不同时段的干涉像对
图4  地面沉降速率统计学检验(a) 南沙区地面沉降速率分布图 (b) Sentinel-1数据VV、VH不同极化方式SBAS-InSAR结果的比较
图5  地面沉降率实地检验(a)历史水准数据验证 (b)教学楼地面沉降
图6  地面沉降速率空间分布 审图号:粤S(2020)01-005(a)2015年6月~2018年4月南沙区年平均地面沉降速率 (b)典型区地面稳定情况
图7  圈层划分示意图
图8  南沙区中心点向外圈层平均沉降速率
图9  重点区域A、B、C、D地面沉降时间序列
1 Yin Yueping, Zhang Zuochen, Zhang Kaijun, Land subsidence and countermeasures for its prevention in China[J]. Chinese Journal of Geological Hazards and Control, 2005, 16(2): 1-8.
1 殷跃平,张作辰,张开军.我国地面沉降现状及防治对策研究[J].中国地质灾害与防治学报, 2005, 16(2): 1-8.
2 Kooi H. Land subsidence due to compaction in the coastal area of the Netherlands: the role of lateral fluid flow and constraints from well-log data[J]. Global and Planetary Change, 2000,27(1):207-222. DOI:10.1016/S0921-8181(01)00067-4.
doi: 10.1016/S0921-8181(01)00067-4
3 Yang Mengshi, Liao Mingsheng, Qin Xiaoqiong, et al. Analysis of capabilities of C and L-band SAR data to detect new-ly-reclaimed area[J]. Geomatics and Information Science of Wuhan University,2017,42(9):1300-1305.
3 杨梦诗,廖明生,秦晓琼,等.C和L波段SAR数据在填海新区的应用及特性分析[J].武汉大学学报(信息科学版),2017,42(9):1300-1305.
4 Takagi H, Esteban M, Mikami T, et al. People's perception of land subsidence, floods, and their connection: a note based on recent surveys in a sinking coastal community in Jakarta[J]. Ocean & Coastal Management,2021,211:105753. DOI:10.1016/j.ocecoaman.2021.105753.
doi: 10.1016/j.ocecoaman.2021.105753
5 Zhu Jianjun, Li Zhiwei, Hu Jun. Research progress and methods of InSAR for deformation monitoring[J]. Acta Geodaetica et Cartographica Sinica, 2017,46 (10) : 1717-1733.
5 朱建军,李志伟,胡俊. InSAR变形监测方法与研究进展[J].测绘学报, 2017,46(10):1717-1733.
6 Berardino P, Fornaro G, Lanari R, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11):2375-2383. DOI: 10.1109/TGRS.2002.803792
doi: 10.1109/TGRS.2002.803792
7 Mingliang G , Huili G , Beibei C , et al. Regional land subsidence analysis in eastern Beijing Plain by InSAR time series and wavelet transforms[J]. Remote Sensing, 2018, 10(3):365.DOI: 10.3390/rs10030365.
doi: 10.3390/rs10030365
8 Li Shanshan, Li Zhiwei, Hu Jun, et al. Monitoring of seasonal frozen soil deformation on the Qinghai-Tibet Plateau using SBAS-INSAR technology [J].Chinese Journal of Geophysics, 2013, 56(5):1476-1486.
8 李珊珊,李志伟,胡俊,等. SBAS-InSAR技术监测青藏高原季节性冻土形变[J].地球物理学报,2013, 56(5):1476-1486.
9 Chen Jiwei, Zeng Qiming, Jiao Jian, et al. SBAS time series analysis technique based on Sentinel-1A TOPS SAR images: a case study of Yellow River Delta[J]. Remote Sensing For Land & Resources,2017,29(4): 82-87.
9 陈继伟,曾琪明,焦健,等. Sentinel-1A卫星TOPS模式数据的SBAS时序分析方法——以黄河三角洲地区为例[J].国土资源遥感, 2017,29(4): 82-87.
10 Zhou Lü,Shi Xianjian,Ren Chao,et al. Monitoring of land subsidence in Shenzhen reclamation area based on Sentinel-1aA interferometric synthetic aperture radar[J].Science Technology and Engineering,2021,21( 21) : 8765-8769.
10 周吕, 施显健, 任超,等. 哨兵-1A合成孔径雷达的深圳围填海区域地面沉降监测[J]. 科学技术与工程,2021,21(21): 8765-8769.
11 Lu Wangda,Han Chunming,Yue Xijuan,et al.Land subsidence monitoring in Tianjin with PS-InSAR technique based on Sentinel -1 data[J].Remote Sensing Technology and Application,2020,35(2):416-423.
11 卢旺达,韩春明,岳昔娟,等. 基于Sentinel-1A 数据的天津地区PS-InSAR 地面沉降监测与分析[J]. 遥感技术与应用,2020,35(2):416-423.]
12 Moreira A, Prats-Iraola P, Younis M, et al. A tutorial on synthetic aperture radar[J]. IEEE Geoscience & Remote Sensing Magazine,2013,1(1):6-43. DOI:10.1109/MGRS.2013. 2248301.
doi: 10.1109/MGRS.2013. 2248301
13 Yu Jie, Chen Zuozhi, Xu Shannan. Effects of reclamation on wetland resources and biological resources in Nansha of the Pearl River Estuary[J]. Chinese Fishery Science,2016,23(3):661-671.
13 于杰,陈作志,徐姗楠.围填海对珠江口南沙湿地资源与生物资源的影响[J].中国水产科学,2016,23(3):661-671.
14 Du Haiyan, Zheng Zhuo. New theory on Guangdong geology[M]. Beijing: Geology Press, 2012:17-21.
14 杜海燕,郑卓.广东地质新论[M].北京:地质出版社, 2012: 17-21.
15 Chen Xiaoyue. Surface subsidence characteristics of soft land in Nansha District, Guangzhou and suggestions on urban disaster prevention and mitigation[J]. Geological Hazards and Environmental Protection,2018,29(2):17-22.
15 陈小月.广州市南沙区软土地面沉降特征及城市防灾减灾的建议[J].地质灾害与环境保护,2018,29(2):17-22.
16 Zhou C, Gong H, Chen B, et al. Land subsidence response to different land use types and water resource utilization in Beijing-Tianjin-Hebei,China[J]. Remote Sensing,2020,12(3): 457. DOI:10.3390/rs12030457.
doi: 10.3390/rs12030457
17 Cheng Pu, Xu Caijun, Wang Hua. Research on phase unwrapping algorithm of InSAR [J]. Journal of Geodesy and Geodynamics, 2007, 27(3):50-55.
17 程璞, 许才军, 王华. InSAR相位解缠算法研究[J]. 大地测量与地球动力学, 2007, 27(3):50-55.
18 Lin Hui, Ma Peifeng, Wang Weixi. Urban infrastructure health monitoring with spaceborne multi-temporal synthetic aperture radar interferometry [J].Acta Geodaetica et Cartographica Sinica, 2017,46(10): 1421-1433.
18 林珲, 马培峰, 王伟玺. 监测城市基础设施健康的星载MT-InSAR方法介绍[J]. 测绘学报, 2017,46(10):1421-1433.
19 Xiao Liang, He Yueguang , Xing Xueming , et al. Time series subsidence analysis of drilling solution miningrock salt mines based on Sentinel-1 data and SBAS-InSAR technique[J]. Journal of Remote Sensing, 2019,23(3):501-513.
19 肖亮,贺跃光,邢学敏,等.Sentinel-1和SBAS-InSAR分析钻井水溶岩盐矿山时序沉降[J]. 遥感学报,2019,23(3):501-513.
20 Ge Daqing, Yin Yueping, Wang Yan, et al.He subsidence and ground water level changes monitoring by using coherent target InSAR technique: a case study of Dezhou, Shandong [J]. Remote Sensing for Land and Resources,2014,26(1):103-109.
20 葛大庆,殷跃平,王艳,等. 地面沉降—回弹及地下水位波动的InSAR长时序监测——以德州市为例[J].国土资源遥感,2014,26(1):103-109.
21 Gao Lei, Chen Yunkun, Qu Shangxia, et al. Analysis of land subsidence about soft characteristics and monitoring in Nansha District, Guangzhou[J]. Yangtze River,2020,51(S2):94-97.
21 高磊,陈运坤,屈尚侠,等.广州南沙区软土地面沉降特征及监测预警分析[J].人民长江,2020,51():94-97,154.
22 Zhao Q, Lin H, Jiang L, et al. A study of ground deformation in the Guangzhou urban area with persistent scatterer interferometry[J]. Sensors (Basel),2009,9(1):503-518. DOI:10.3390/s90100503.
doi: 10.3390/s90100503
23 Li J, Zhou L, Ren C, et al. Spatiotemporal inversion and mechanism analysis of surface subsidence in Shanghai area based on time-series InSAR[J]. Applied Sciences, 2021, 11(16): 7460. DOI:10.3390/app11167460.
doi: 10.3390/app11167460
24 Van Der Horst T, Rutten M M, Van De Giesen N C, et al. Monitoring land subsidence in Yangon, Myanmar using Sentinel-1 persistent scatterer interferometry and assessment of driving mechanisms[J].Remote Sensing of Environment, 2018, 217: 101-110. DOI:10.1016/j.rse.2018.08.004.
doi: 10.1016/j.rse.2018.08.004
[1] 杨欣源,白晓静. 基于Sentinel-1和MODIS数据反演农田地表土壤水分—以REMEDHUS地区为例[J]. 遥感技术与应用, 2021, 36(5): 973-982.
[2] 李诗娆,张波,刘国祥,沙永莲,王敏,王晓文,张瑞. 基于NPSI方法的西安市地裂缝灾害链地表形变监测与演化态势分析[J]. 遥感技术与应用, 2021, 36(4): 857-864.
[3] 王晨丞,王永前,王利花. 基于SAR纹理信息的农作物识别研究——以农安县为例[J]. 遥感技术与应用, 2021, 36(2): 372-380.
[4] 张齐民,郑一桐,张露,李治国,闫世勇. 基于时序像素跟踪算法的南伊内里切克冰川运动提取与特征分析[J]. 遥感技术与应用, 2020, 35(6): 1273-1282.
[5] 麻源源,左小清,麻卫峰. 基于PS-InSAR的天津地区沉降监测及分析[J]. 遥感技术与应用, 2019, 34(6): 1324-1331.
[6] 黄静,王芳,张运. 基于PSI技术的芜湖市地面沉降时空特征分析[J]. 遥感技术与应用, 2019, 34(4): 829-838.
[7] 林辉,柯长青. COSMOGSkyMed数据在常州市地表形变监测中的应用[J]. 遥感技术与应用, 2016, 31(3): 599-606.
[8] 雷坤超,贾三满,陈蓓蓓,罗勇,韩征. 基于PS-InSAR技术的廊坊市地面沉降监测研究[J]. 遥感技术与应用, 2013, 28(6): 1114-1119.