测绘通报 ›› 2024, Vol. 0 ›› Issue (2): 74-79.doi: 10.13474/j.cnki.11-2246.2024.0213

• 学术研究 • 上一篇    下一篇

基于InSAR技术的天津局部地表沉降特征分析

张倩1,2, 马悦1,2, 周洪月3, 闫世勇1,2   

  1. 1. 中国矿业大学环境与测绘学院, 江苏 徐州 221116;
    2. 自然资源部国土环境与灾害监测重点实验室, 江苏 徐州 221116;
    3. 天津市测绘院有限公司, 天津 300041
  • 收稿日期:2023-08-07 出版日期:2024-02-25 发布日期:2024-03-12
  • 作者简介:张倩(2000—),女,硕士生,主要研究方向为地质灾害监测。E-mail:zhang_qian@cumt.edu.cn
  • 基金资助:
    国家重点研发计划“政府间国际科技创新合作”重点专项项目(2022YFE0102600)

Analysis of local surface subsidence characteristics in Tianjin based on InSAR technology

ZHANG Qian1,2, MA Yue1,2, ZHOU Hongyue3, YAN Shiyong1,2   

  1. 1. School of Environment and Spatial informatics, China University of Mining and Technology, Xuzhou 221116, China;
    2. College of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;
    3. Tianjin Surveying and Mapping Institute Co., Ltd., Tianjin 300041, China
  • Received:2023-08-07 Online:2024-02-25 Published:2024-03-12

摘要: 天津是我国地面沉降最严重的地区之一。本文基于融合分布式的DS-InSAR技术处理了2021年1月—2023年6月的58景Sentinel-1A数据,获取了天津南部地区最新地表形变特征;并结合土地覆盖和水文地质等信息,开展了天津市典型沉降成因分析。结果表明:①天津地面沉降分布差异性较大,不均匀沉降特征明显,西南部地区为沉降重灾区,最大沉降速率达85.2 mm/a;②天津地面沉降与地下水过度开采、地面载荷增加及地质构造密切相关。该研究可为天津市地质灾害防治提供数据支撑和决策依据。

关键词: DS-InSAR, D-InSAR, 天津, 地面沉降, 特征分析

Abstract: Tianjin is one of the areas in our country with the most severe ground subsidence. This article is based on the integrated distributed scatterer interferometry (DS-InSAR) technology, which processed 58 scenes of Sentinel-1A data from January 2021 to June 2023. It obtained the latest surface deformation characteristics in the southern region of Tianjin. By combining information on land use, hydrogeology, and other factors, a typical subsidence analysis was conducted. The results are as follows:①There is significant variation in the distribution of ground subsidence in Tianjin, with obvious uneven subsidence characteristics. The southwestern region is the most severely affected area, with a maximum subsidence rate of 85.2 mm/a. ②The ground subsidence in Tianjin is closely related to excessive groundwater extraction, increased surface loading, and geological structures. This study provides data support and decision-making basis for geological disaster prevention and control in Tianjin.

Key words: DS-InSAR, D-InSAR, Tianjin, land subsidence, feature analysis

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