1. 广东工业大学 土木与交通工程学院,广东,广州,510006
2. 广东工业大学 大湾区城市环境安全与绿色发展教育部重点实验室,广东,广州,510006
陈佳炜(1997–),男,硕士研究生,主要研究方向为InSAR与地表形变监测
吴希文(1983–),男,教授,博士生导师,主要研究方向为InSAR与地表形变监测,E-mail:hayman.ng@foxmail.com
网络首发:2022-05-10,
纸质出版:2022
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陈佳炜, 吴希文, 王华, 陈炳杰. 基于双极化时序InSAR技术的地表形变监测[J]. 广东工业大学学报, 2022, 39(3): 77-82.
Chen Jia-wei, Ng Alex Hay-Man, Wang Hua, et al. Surface Deformation Monitoring Based on Dual-polarization Time Series InSAR Technology[J]. 2022, 39(3): 77-82.
陈佳炜, 吴希文, 王华, 陈炳杰. 基于双极化时序InSAR技术的地表形变监测[J]. 广东工业大学学报, 2022, 39(3): 77-82. DOI: 10.12052/gdutxb.210084.
Chen Jia-wei, Ng Alex Hay-Man, Wang Hua, et al. Surface Deformation Monitoring Based on Dual-polarization Time Series InSAR Technology[J]. 2022, 39(3): 77-82. DOI: 10.12052/gdutxb.210084.
针对时序干涉测量(Time-series Interferometric Synthetic Aperture Radar,TS-InSAR)技术在相干性较差地区监测结果不佳的问题,从极化数据的角度对传统TS-InSAR方法进行改进。实验选取珠海市高栏港经济区作为研究区域,以47景含有垂直发射垂直接收模式(Vertical transmit and Vertical receive,VV)和垂直发射水平接收模式(Vertical transmit and Horizontal receive,VH)的双极化Sentinel-1A卫星影像作为数据源进行实验,并对实验结果进行验证分析。结果表明:采用双极化数据能够有效提高时序InSAR技术的监测质量;造成该地区沉降的原因是地质条件和填海工程。该研究可为地区沉降监测和防治提供理论依据。
To solve the problem of poor monitoring results generated by time-series Interferometric Synthetic Aperture Radar (TS-InSAR) technology in low coherence areas
the traditional TS-InSAR method is improved from the perspective of polarization data. Taking Zhuhai Gaolan Port Economic Zone as the research subject
the article examines 47 dual-polarized Sentinel-1A satellite images with vertical-transmit-and-vertical-receive mode (VV) and vertical-transmit-and-horizontal-receive mode (VH) to experiment and obtain results and do the validation analysis. Results show that the monitoring quality of the time series InSAR technology can be effectively improved by applying dual-polarization data; and that the subsidence in this area is caused by geological conditions and reclamation projects. This research can provide a theoretical basis for the monitoring and prevention of regional subsidence.
LIU S N, TAO J, LU Y H. Multi-source data fusion analysis of land subsidence monitoring [J]. Bulletin of Surveying and Mapping, 2020(12): 46-49.
DOU C, ZHAO L J, ZHANG S P, et al . Study on surface settlement of Golmud city based on time series InSAR [J ] . Bulletin of Surveying and Mapping, 2020(10): 123-126.
ZHU J J, LI Z W, HU J. Research progress and methods of InSAR for deformation monitoring [J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1717-1733.
NG A H. Advanced satellite radar interferometry for ground surface displacement detection[D]. Sydney: The University of New South Wales, 2010.
SHI X J, REN C, ZHOU L, et al . Land subsidence inversion analysis along the subway in the reclamation area based on InSAR [J ] . Science of Surveying and Mapping, 2021, 46(2): 146-151.
LIU Q, YUE G S, DING X B, et al . Temporal and spatial characteristics analysis of deformation along Foshan subway using time series InSAR [J ] . Geomatics an d Information Science of Wuhan University, 2019, 44(7): 1099-1106.
ZHANG W T, JI L Y, ZHU L Y, et al . Current crustal deformation of Yinchuan basin based on Sentinel-1 data [J ] . Journal of Geodesy and Geodynamics, 2020, 40(9): 902-906.
FERRETTI A, PRATI C, ROCCA F. Permanent scatterers in SAR interferometry [J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(1): 8-20.
KAMPES B M. Radar Interferometry: Persistent Scatterer Technique[M]. The Netherland: Springer-Verlag, 2006: 15-28.
HOOPER A J. Persistent scatterer radar interferometry for crustal deformation studies and modelling of volcanic deformation[D]. Palo Alto: Stanford University, 2006.
NG A H, GE L L, LI X J, et al . Monitoring ground deformation in Beijing, China with persistent scatterer SAR interferometry [J ] . Journal of Geodesy, 2012, 86(6): 375-392.
CLOUDE S R, PAPATHANASSIOUS K P. Polarimetric SAR interferometry [J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(5): 1551-1565.
PIPIA L, FABREGAS X, AGUASCA A, et al . Polarimetric differential SAR interferometry: first results with ground-based measurements [J ] . IEEE Geoscience and Remote Sensing Letters, 2009, 6(1): 167-171.
NAVARRO-SANCHEZ V D, LOPEZ-SANCHEZ J M, VINCENTE-GUIJALBA F. A contribution of polarimetry to satellite differential SAR interferometry: increasing the number of pixel candidates [J]. IEEE Geoscience and Remote Sensing Letters, 2010, 7(2): 276-280.
IGLESIAS R, MALLORQUI J J, LÓPEZ-DEKKER P. DInSAR pixel selection based on sublook spectral correlation along time [J]. IEEE Transactions on Geoscience Remote Sensing, 2014, 52(7): 3788-3799.
ZHAO F, MALLORQUI J J. Coherency matrix decomposition-based polarimetric persistent scatterer interferometry [J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(10): 7819-7831.
ZHANG Y M. Analysis on settlement disaster and prevention of under consolidation soft soil foundation in western district of Zhuhai [J]. Guangdong Architecture Civil Engineering, 2010, 17(6): 11-13.
JIANG J J, LIU J, WU S T, et al . Distribution characteristics of soft soil and risk assess ment of soft soil subsidence in Zhuhai [J ] . Journal of Geological Hazards and Environment Preservation, 2020, 31(2): 68-74.
MULLISSA A G, TOLPEKIN V, STEIN A, et al . Polarimetric differential SAR interferometry in an arid natural environment [J ] . International Journal of Applied Earth Observation and Geoinformation, 2017, 59: 9-18.
ESMAEILI M, MOTAGH M. Improved persistent scatterer analysis using amplitude dispersion index optimization of dual polarimetry data [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 117: 108-114.
AZADNEJAD S, MAGHSOUDI Y, PERISSIN D. Evaluation of polarimetric capabilities of dual polarized Sentinel-1 and TerraSAR-X data to improve the PSInSAR algorithm using amplitude dispersion index optimization [J]. International Journal of Applied Earth Observation and Geoinformation, 2020, 84: 101950.
LAI B, JIANG J J, LIU J. Analysis of ground subsidence monitoring in Zhuhai city base on PS-InSAR technology [J]. Resources Environment and Engineering, 2021, 35(2): 241-244.
LI Z B, DANG X H, CAI M X, et al . Subsidence monitoring and analysis of Zhuhai based on PSInSAR technology [J ] . Journal of Natural Disasters, 2021, 30(1): 38-46.
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