测绘通报 ›› 2021, Vol. 0 ›› Issue (6): 71-75.doi: 10.13474/j.cnki.11-2246.2021.0179

• 区域形变监测成果 • 上一篇    下一篇

利用多传感器SAR数据集监测城市地面沉降

祝昕刚, 李更尔   

  1. 广东省地质测绘院, 广东 广州 510800
  • 收稿日期:2021-04-16 修回日期:2021-04-22 发布日期:2021-06-28
  • 作者简介:祝昕刚(1971—),男,高级工程师,从事工程测量、地理信息系统工程、不动产测绘、生产技术管理、测绘产品质检等工作。E-mail:327692975@qq.com

Urban land subsidence monitoring using multi-sensor SAR datasets

ZHU Xingang, LI Geng’er   

  1. Geology Surveying and Mapping Institute of Guangdong, Guangzhou 510800, China
  • Received:2021-04-16 Revised:2021-04-22 Published:2021-06-28

摘要: 在过去的几十年中,洛杉矶由于自然灾害、城市建设、地下水开采和石油开采等人为因素而发生了严重的地表变形。本文的目的是绘制洛杉矶地表形变速率分布图,并使用改进的小基线集(SBAS)技术和多传感器SAR数据集,分析该地区2003年10月至2017年10月的形变原因。同时,将SBAS反演的变形结果、GPS测量结果和多传感器SAR数据集的变形结果进行了比较,结果高度一致。结果显示,2003—2017年,洛杉矶多个地区发生沉降抬升,最大累计沉降量为-266.8 mm,年平均沉降速度为-19 mm/a,主要是由地下水过度开采造成的。最大累计抬升量为104.8 mm,年平均抬升速度可达7.5 mm/a。该研究结果具有良好的实际应用价值,可为当地政府的防灾减灾提供重要依据。

关键词: SBAS, 多传感器SAR数据, 地表变形, 地面沉降

Abstract: In the past few decades, Los Angeles has occurred severe surface deformation due to human factors such as natural disasters, urban construction, groundwater extraction and oil extraction. The purpose of this study is to map the distribution of surface deformation rates in Los Angeles, and use improved SBAS (small baseline set) technology and multi-sensor SAR data sets to analyze the causes of deformation in the area from October 2003 to October 2017. At the same time, the deformation results of SBAS inversion, GPS measurement results and the deformation results of the multi-sensor SAR data set are compared, and the results are highly consistent. The results show that between 2003 and 2017, settlement and uplift occurred in many areas of Los Angeles. The maximum cumulative settlement was -266.8 mm, and the annual average settlement rate was -19 mm/a, which was mainly caused by the excessive exploitation of groundwater. The maximum cumulative up lift was 104.8 mm, and the annual average uplift speed could reach 7.5 mm/a. The research results have good practical application value and can provide an important basis for the local government’s disaster prevention and mitigation.

Key words: SBAS, multi-sensor SAR data, ground deformation, land subsidence

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