基于InSAR技术的地表形变监测与影响因素分析

胡波; 陈邦鑫

doi:10.12052/gdutxb.220101

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基于InSAR技术的地表形变监测与影响因素分析

更新时间：2026-05-27

- 基于InSAR技术的地表形变监测与影响因素分析
- Surface Deformation Monitoring and Influencing Factor Analysis Based on InSAR Technology
- 广东工业大学学报 2023年40卷第1期页码：83-91
- 作者机构：
  
  广东工业大学土木与交通工程学院,广东,广州,510006
- 作者简介：
  
  胡波(1983–)，男，副教授，硕士生导师，主要研究方向为InSAR变形监测的理论和应用，E-mail：hubo@gdut.edu.cn
- 基金信息：
  
  国家重点研发项目(2017YFA0603103);国家自然科学基金资助项目(41204012，41974009，41431070，41590854，41674006);福建省科技计划项目(2017Y3004);中国科学院前沿科学重点研究项目(QYZDB-SSW-DQC027，QYZDJ-SSW-DQC042);大地测量与地球动力学国家重点实验室开放基金资助项目(SKLGED2020-2-3-E);广州市科学技术规划项目(202102080682)
- DOI：10.12052/gdutxb.220101
  中图分类号： TU196
- 网络首发：2023-01-25，
  
  纸质出版：2023
- 稿件说明：
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胡波, 陈邦鑫. 基于InSAR技术的地表形变监测与影响因素分析[J]. 广东工业大学学报, 2023, 40(1): 83-91.

Hu Bo, Chen Bang-xin. Surface Deformation Monitoring and Influencing Factor Analysis Based on InSAR Technology[J]. 2023, 40(1): 83-91.
胡波, 陈邦鑫. 基于InSAR技术的地表形变监测与影响因素分析[J]. 广东工业大学学报, 2023, 40(1): 83-91. DOI： 10.12052/gdutxb.220101.

Hu Bo, Chen Bang-xin. Surface Deformation Monitoring and Influencing Factor Analysis Based on InSAR Technology[J]. 2023, 40(1): 83-91. DOI： 10.12052/gdutxb.220101.

摘要

地表形变引发的地质灾害屡见不鲜，尤其是在城市区域，其严重阻碍了城市化的可持续发展。为了评估城市地表形变引发地质灾害的风险，高时间空间分辨率的地表形变监测分析变得尤为重要。本文基于2019年1月至2021年1月的Sentinel-1A卫星影像，利用SBAS-InSAR以及PS-InSAR技术获取南昌市地表形变的时间序列，并结合小波周期分析和灰色关联度分析评估形变区域与气候环境的相关性。研究表明，南昌市的中心城区受到城市建设和黏土层厚度的影响，表现出大范围的沉降信号；东南部的农业生态地区由于地下水的补充而表现出抬升的信号。周期分析进一步表明南昌市地表形变皆受降水量变化的影响。本研究结合外部数据，从多个角度考察了地铁线路在变形幅度较大的地区发生沉降灾害的可能性，为防灾减灾提供参考。

Abstract

Geological disasters caused by surface deformation are common

especially in urban areas

which seriously hinders the sustainable development of urbanization. In order to evaluate the risk of geological disasters caused by urban surface deformation

monitoring and analysis with high temporal and spatial resolution becomes particularly important. Based on Sentinel-1A satellite images from January 2019 to January 2021

SBAS InSAR and PS InSAR technology is used to obtain the time series of surface deformation in Nanchang

and wavelet periodic analysis and grey correlation analysis combined to evaluate the correlation between deformation area and climate environment. The research shows that the central urban area of Nanchang is affected by urban construction and clay layers

showing a large-scale subsidence signal; the agro-ecological areas in the southeast show uplift signals due to groundwater replenishment. Periodic analysis further shows that the surface deformation of Nanchang is affected by the change of precipitation. Combined with external data

this study examines the possibility of subsidence disasters of subway lines in areas with large deformation from multiple perspectives

thus providing reference for disaster prevention and reduction.

关键词

Keywords

references

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