Ground Deformation Monitoring and Influencing Factors Analysis in Fuzhou City Based on PSI Technology

Zhou Peipei; Ng Alex Hayman; Wang Hua; Du Zheyuan

doi:10.12052/gdutxb.240064

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Ground Deformation Monitoring and Influencing Factors Analysis in Fuzhou City Based on PSI Technology

更新时间：2026-05-27

- Ground Deformation Monitoring and Influencing Factors Analysis in Fuzhou City Based on PSI Technology
- Vol. 43, Issue 2, Pages: 128-136(2026)
- 作者机构：
  
  1. 广东工业大学土木与交通工程学院,广东,广州,510006
  2. 华南农业大学资源环境学院,广东,广州,510642
  3. 新南威尔士大学土木与环境工程学院, 新南威尔士州悉尼 NSW,2052
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.240064
  CLC： TU196
- Published：2026
- 稿件说明：
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周佩佩, 吴希文, 王华, 等. 基于PSI技术的福州市地面形变监测与影响因素分析[J]. 广东工业大学学报, 2026, 43(2): 128–136.

Zhou Peipei, Ng Alex Hayman, Wang Hua, et al. Ground Deformation Monitoring and Influencing Factors Analysis in Fuzhou City Based on PSI Technology[J]. 2026, 43(2): 128-136.
周佩佩, 吴希文, 王华, 等. 基于PSI技术的福州市地面形变监测与影响因素分析[J]. 广东工业大学学报, 2026, 43(2): 128–136. DOI： 10.12052/gdutxb.240064

Zhou Peipei, Ng Alex Hayman, Wang Hua, et al. Ground Deformation Monitoring and Influencing Factors Analysis in Fuzhou City Based on PSI Technology[J]. 2026, 43(2): 128-136. DOI： 10.12052/gdutxb.240064.

摘要

使用永久散射体干涉测量(Persistent Scatterer Interferometric，PSI) 技术对福州市2018年1月至2023年6月的66景Sentinel-1A数据进行处理和分析，以获取地面形变监测结果，并通过交叉验证确保结果的精度。研究得到福州市整体形变速率在−44 ~18 mm/a之间，存在5个沉降较为明显的区域，其中4个靠近地铁线路，最大沉降位于长乐区峡漳路与福北路交界处。该地区的沉降是自然因素与人为因素共同作用的结果。从自然因素来看，沉降主要发生在第四纪沉积物地区；而人为因素则主要包括地铁建设、房屋建造与拆除等建设活动，以及仓库作业中货物装卸导致的地面荷载变化。该研究结果可以为福州市的城市规划建设和沉降灾害预防管理提供参考依据。

Abstract

In this research

66 Sentinel-1 images spanning from January 2018 to June 2023 were analyzed using Persistent Scatterer Interferometric (PSI) technology to map ground deformation in Fuzhou City. The accuracy of the results was demonstrated by cross-validation. The study reveals that the overall deformation rate in Fuzhou City ranges from −44~18 mm/a

with five distinct regions experiencing significant ground subsidence. Among these

four regions are located near subway lines

and the maximum subsidence occurs at the intersection of Xiazhang Road and Fubei Road in Changle District. The occurrence of subsidence in Fuzhou is the consequence of a complex interplay between natural and anthropogenic factors. In terms of natural factors

the subsidence is primarily distributed in areas with Quaternary sediments. The anthropogenic factors primarily include construction activities such as subway construction

building construction and demolition

as well as changes in ground loading due to warehouse operations such as cargo loading and unloading. The study results can provide a reference basis for urban construction and prevention management of subsidence disasters in Fuzhou.

关键词

Keywords

references

ORHAN O, OLIVER-CABRERA T, WDOWINSKI S, et al . Land subsidence and its relations with sinkhole activity in Karapınar region, Turkey: a multi-sensor InSAR time series study[J ] . Sensors, 2021, 21(3): 774.

WU P C, WEI M, D’HONDT S. Subsidence in coastal cities throughout the world observed by InSAR[J]. Geophysical Research Letters, 2022, 49(7): e2022GL098477.

NAVARRO-HERNÁNDEZ M I, VALDES-ABELLAN J, TOMÁS R, et al . Analysing the impact of land subsidence on the flooding risk: evaluation through InSAR and modelling[J ] . Water Resources Management, 2 023, 37(11): 4363-4383.

CHI Y X. Analysis of influence factors for land subsidence in Fuzhou[J]. Hydrogeology Engineering Geology, 2009, 36(6): 131-133.

FAN X P, HUANG W S. Urban environmental problems caused by the exploitation of geothermal water──a case study of Fuzhou[J]. Acta Geographica Sinica, 1995, 50(1): 13-14.

FAN X F, WU Z X, JIAN W B. Analysis of the ground subsidence in the hot spring area, Fuzhou[J]. Journal of Geological Hazards and Environment Preservation, 2004, 15(2): 89-92.

FAN X F, WU Z X, JIAN W B, et al . Finite element numerical simulation of the geothermal water system in the hot spring area in Fuzhou[J ] . Journal of Fuzhou University (Natural Science Edition) , 2005, 33(2): 226-229.

FERRETTI A, PRATI C, ROCCA F. Permanent scatterers in SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(1): 8-20.

TOMÁS R, ROMERO R, MULAS J, et al . Radar interferometry techniques for the study of ground subsidence phenomena: a review of practical issues through cases in Spain[J ] . Environmental Earth Sciences, 2014, 71(1): 163-181.

LAN H X, MENG Y S, ZHANG Y X. Spatiotemporal evolution analysis of land subsidence in Fuzhou city under the influence of complex factors[J]. Journal of Engineering Geology, 2019, 27(6): 1350-1361.

HU B, YANG B, ZHANG X, et al . Time-series displacement of land subsidence in Fuzhou downtown, monitored by SBAS-InSAR technique[J ] . Journal of Sensors, 2019(1): 3162652.

HUANG H, XUE D, ZHUO G, et al . Monitoring land subsidence in Fuzhou city (China) using the SBAS-InSAR method with Sentinel-1 imagery data[C ] //2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) . Xiamen: IEEE, 2019: 1-5.

ZHENG W P, ZHANG S C, WANG Y P, et al . Spatiotemporal variation of surface subsidence in Fuzhou interpreted by SBAS-InSAR[J ] . Science of Surveying and Mapping, 2022, 47(3): 103-109.

ZHU Y Y, HE Y, LI H Y, et al . Land Subsidence Monitoring and analysis in Fuzhou based on InSAR and multispectral remote sensing technology[J ] . International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences-ISPRS Archives, 2022, 43: 373-379.

RABUS B, EINEDER M, ROTH A, et al . The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar[J ] . ISPRS Journal of Photogrammetry and Remote Sensing, 2003, 57(4): 241-262.

NG A H M. Advanced satellite radar interferometry for ground surface displacement detection[D]. Sydney: the University of New South Wales, 2010.

FERRETTI A, PRATI C, ROCCA F. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(5): 2202-2212.

KAMPES B M. Radar interferometry[M]. Dordrecht, The Netherlands: Springer, 2006: 211.

ROSEN P A, GURROLA E, SACCO G F, et al . The InSAR scientific computing environment[C ] //EUSAR 2012; 9th European Conference on Synthetic Aperture Radar. Nuremberg: VDE, 2012: 730-733.

KAMPES B M, HANSSEN R F. Ambiguity resolution for permanent scatterer interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(11): 2446-2453.

NG A H M, GE L, LI X, et al . Monitoring ground deformation in Beijing, China with persistent scatterer SAR interferometry[J ] . Journal of Geodesy, 2012, 86(6): 375-392.

COSTANTINI M, ROSEN P A. A generalized phase unwrapping approach for sparse data[C]//IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99. Hamburg: IEEE, 1999, 1: 267-269.

FERNÁNDEZ-TORRES E A, CABRAL-CANO E, NOVELO-CASANOVA D A, et al . Risk assessment of land subsidence and associated faulting in Mexico City using InSAR[J ] . Natural Hazards, 2022, 112(1): 37-55.

张路. 福建东南沿海盆地第四纪构造运动模式与动力学成因[D]. 北京: 中国地震局地质研究所, 2008.

XU X, ZHAO D, MA C, et al . Monitoring subsidence deformation of Suzhou subway using InSAR timeseries analysis[J ] . IEEE Access, 2020, 9: 3400-3416.

CAO Q, ZHANG Y, YANG L, et al . Unveiling the driving factors of urban land subsidence in Beijing, China[J ] . Science of the Total Environment, 2024, 916: 170134.

LIU Z, NG A H M, WANG H, et al . Land subsidence modeling and assessment in the West Pearl River D elta from combined InSAR time series, land use and geological data[J ] . International Journal of Applied Earth Observation and Geoinformation, 2023, 118: 103228.

SUN H, PENG H, ZENG M, et al . Land subsidence in a coastal city based on SBAS-InSAR monitoring: a case study of Zhuhai, China[J ] . Remote Sensing, 2023, 15(9): 2424.

HE Y, NG A H M, Wang H, et al . Understanding the spatiotemporal characteristics of land subsidence and rebound in the Lianjiang plain using time-series InSAR with dual-track sentinel-1 data[J ] . Remote Sensing, 2023, 15(13): 3236.

HUANG Z, YU F. InSAR-derived surface deformation of Chaoshan Plain, China: exploring the role of human activities in the evolution of coastal landscapes[J]. Geomorphology, 2023, 426: 108606.

JULONG D. The GRA in cause-effect space of resources[J]. Journal of Grey System, 2009, 21(2): 113-118.

HU B, CHEN B X. Surface deformation monitoring and influencing factor analysis based on InSAR technology[J]. Journal of Guangdong University of Technology, 2023, 40(1): 83-91.

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