HAN Peng, YANG Xiaoxia, BAI Lin, SUN Qishi. The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method[J]. Acta Oceanologica Sinica, 2017, 36(7): 110-118. doi: 10.1007/s13131-017-1087-y
Citation: HAN Peng, YANG Xiaoxia, BAI Lin, SUN Qishi. The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method[J]. Acta Oceanologica Sinica, 2017, 36(7): 110-118. doi: 10.1007/s13131-017-1087-y

The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method

doi: 10.1007/s13131-017-1087-y
  • Received Date: 2017-01-17
  • Rev Recd Date: 2017-04-07
  • Time-series InSAR analysis (e.g., permanent scatterers (PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar (DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers (DSs). Twenty-four scenes of COSMO-SkyMed images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers (PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with ±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate –30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions.
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  • Bai Lin, Jiang Liming, Wang Haisheng, et al. 2016. Spatiotemporal characterization of land subsidence and uplift (2009–2010) over Wuhan in Central China revealed by TerraSAR-X InSAR analysis. Remote Sensing, 8(4): 350
    Berardino P, Fornaro G, Lanari R, et al. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11): 2375-2383
    Bohannon J. 2010. The Nile Delta’s sinking future. Science, 327(5972): 1444-1447
    Cao Ning, Lee H, Jung H C. 2016. A phase-decomposition-based PSInSAR processing method. IEEE Transactions on Geoscience and Remote Sensing, 54(2): 1074-1090
    Chaussard E, Bürgmann R, Shirzaei M, et al. 2014. Predictability of hydraulic head changes and characterization of aquifer-system and fault properties from InSAR-derived ground deformation. Journal of Geophysical Research: Solid Earth, 119(8): 6572-6590
    Dai Keren, Liu Guoxiang, Li Zhenhong, et al. 2015. Extracting vertical displacement rates in Shanghai (China) with multi-platform SAR images. Remote Sensing, 7(8): 9542-9562
    De Zan F, Rocca F. 2005. Coherent processing of long series of SAR images. In: the IEEE International Geoscience and Remote Sensing Symposium(IGARSS 2005). Seoul, South Korea: Institute of Electrical and Electronics Engineers Inc, 1987–1990
    Ferretti A, Fumagalli A, Novali F, et al. 2011. A new algorithm for processing interferometric data-stacks: SqueeSAR. IEEE Transactions on Geoscience and Remote Sensing, 49(9): 3460-3470
    Ferretti A, Prati C, Rocca F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8-20
    Fu Cifu, Yu Fujiang, Wang Peitao, et al. 2013. A study on extratropical storm surge disaster risk assessment at Binhai New Area. Haiyang Xuebao (in Chinese), 35(1): 55-62
    Goel K, Adam N. 2012. An advanced algorithm for deformation estimation in non-urban areas. ISPRS Journal of Photogrammetry and Remote Sensing, 73: 100-110
    Hooper A. 2008. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophysical Research Letters, 35(16): L16302
    Hooper A, Bekaert D, Spaans K, et al. 2012. Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics, 514–517: 1-13
    Hooper A, Segall P, Zebker H. 2007. Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos. Journal of Geophysical Research: Solid Earth (1978–2012), 112(B7): B07407
    Hooper A, Zebker H, Segall P, et al. 2004. A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophysical Research Letters, 31(23): L23611
    Jiang Mi, Ding Xiaoli, He Xiufeng, et al. 2016. FaSHPS-InSAR technique for distributed scatterers: A case study over the lost hills oil field, California. Chinese Journal of Geophysics (in Chinese), 59(10): 3592-3603
    Jiang Liming, Lin Hui. 2010. Integrated analysis of SAR interferometric and geological data for investigating long-term reclamation settlement of Chek Lap Kok Airport, Hong Kong. Engineering Geology, 110(3–4): 77-92
    Jiang Liming, Lin Hui, Cheng Shilai. 2011a. Monitoring and assessing reclamation settlement in coastal areas with advanced InSAR techniques: Macao city (China) case study. International Journal of Remote Sensing, 32(13): 3565-3588
    Jiang Liming, Lin Hui, Ma Jianwei, et al. 2011b. Potential of small-baseline SAR interferometry for monitoring land subsidence related to underground coal fires: Wuda (northern China) case study. Remote Sensing of Environment, 115(2): 257-268
    Lee J S, Pottier E. 2009. Polarimetric Radar Imaging: From Basics to Applications,: 53-60
    Lin Hui, Jiang Liming, Zhao Qing. 2007. City ground subsidence and monitoring using D-InSAR. Seminar on Disaster Risk Management and Application of Spatial Information Technology in Disaster Prevention and Mitigation (in Chinese). Beijing: China Association for Disaster Prevention
    Liu Zhiwei, Zhou Huina, Yu Jia. 2016. Evolution analysis of land development and utilization in Zhejiang Beach Recla mation area based on remote sensing technology: taking Shangyu in Zhejiang Province for example. Zhejiang Hydrotechnics (in Chinese),(2): 49-52, 67
    Luo Qingli, Perissin D, Zhang Yuanzhi, et al. 2014. L-and X-band multi-temporal InSAR analysis of Tianjin subsidence. Remote Sensing, 6(9): 7933-7951
    Nicholls R J, Cazenave A. 2010. Sea-level rise and its impact on coastal zones. Science, 328(5985): 1517-1520
    Prati F, Regar E, Mintz G S, et al. 2010. Expert review document on methodology, terminology, and clinical applications of optical coherence tomography: physical principles, methodology of image acquisition, and clinical application for assessment of coronary arteries and atherosclerosis. European Heart Journal, 31(4): 401-415
    Raucoules D, Bourgine B, De Michele M, et al. 2009. Validation and intercomparison of persistent scatterers interferometry: PSIC4 project results. Journal of Applied Geophysics, 68(3): 335-347
    Seiler M C, Seiler F A. 1989. Numerical recipes in C: the art of scientific computing. Risk Analysis, 9(3): 415-416
    Stephens M A. 1970. Use of the Kolmogorov-Smirnov, Cramér-Von Mises and related statistics without extensive tables. Journal of the Royal Statistical Society: Series B. Methodological, 32: 115-122
    Törnqvist T E, Wallace D J, Storms J E A, et al. 2008. Mississippi Delta subsidence primarily caused by compaction of Holocene strata. Nature Geoscience, 1(3): 173-176
    Wang Mingzhou, Li Tao, Jiang Liming, et al. 2016. An improvedment coherent targets technology for monitoring surface deformation. Acta Geodaetica et Cartographica Sinica (in Chinese), 45(1): 36-43
    Wang H, Wright T J, Yu Y P, et al. 2012. InSAR reveals coastal subsidence in the Pearl River Delta, China. Geophysical Journal International, 191(3): 1119-1128
    Yang Lijun. 2003. Engineering geological features and ground treatment in the urban of Shaoxing city (in Chinese) [dissertation]. Hangzhou: Zhejiang University
    Yuan Shun, Zhao Xin, Li Linlin. 2016. Combination evaluation and case analysis of vulnerability of storm surge in coastal provinces of China. Haiyang Xuebao (in Chinese), 38(2): 16-24
    Zheng Xianxin, Wu Qiang, Ying Yufei, et al. 2002. Problems on land subsidence in China’s coastal areas in the 21st century and their solutions. Science & Technology Review (in Chinese),(9): 47-50
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