Surface deformation analysis of Hohhot urban area based on SAR data from Sentinel-1A
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摘要: 为了实现对呼和浩特市城区形变监测，采用永久散射体合成孔径雷达干涉测量（PS-InSAR）技术，对2017年3月—2021年4月期间25景呼和浩特市城区Sentinel-1A数据进行时序干涉处理，提取了城区地表沉降信息，并分析了主要沉降中心沉降原因。结果表明：呼和浩特市城区地表存在5个明显的沉降中心，整体地表平均年沉降速率3.65 mm/a，平均累计沉降量为15.50 mm，其沉降主要原因是由于地下水过度开采。Sentinel-1A数据具有时间基线短、影像数量足、数据免费等优点，利于InSAR时序分析，可满足同类城区地表形变监测工作，服务城市安全。
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关键词:
- 地表沉降 /
- Sentinel-1A /
- 时序分析 /
- 永久散射体干涉技术 /
- 呼和浩特
Abstract: In order to realize the monitoring of deformation in the urban area of Hohhot city, this paper uses the permanent scatterer synthetic aperture radar interferometry （PS-InSAR） technique to perform temporal interferometric processing on 25 scenes of Sentinel-1A data from March 2017 to April 2021 in the urban area of Hohhot city to extract the surface subsidence information in the urban area and analyze the causes of subsidence in the main subsidence centers. The results show that there are five obvious centres of subsidence in the urban area of Hohhot, and that the overall average annual surface subsidence rate is 3.65 mm/a, with an average cumulative subsidence of 15.50 mm. The subsidence is mainly due to over-exploitation of groundwater. Given that the free Sentinel-1A data has the advantages of short time baseline and sufficient number of images, it is conducive to InSAR time series analysis, which can meet similar urban surface deformation monitoring work and serve urban safety.-
Key words:
- ground subsidence /
- Sentinel-1A /
- time series analysis /
- permanent scatterer interferometry /
- Hohhot
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图 3 呼和浩特市2017—2021年地表累计形变量
Figure 3. Cumulative surface settlement of Hohhot City from 2017 to 2021
图 4 2017—2021年研究区平均形变速率图
Figure 4. Average settlement rate of the study area from 2017 to 2021
图 6 实地调查照片
Figure 6. Field photos of concrete building cracks due to ground settlement
表 1 研究所采用的Sentinel-1A数据参数
Table 1. Summary of the Sentinel-1A data parameters used in the study
影像编号 成像日期 空间基线距/m 时间基线距/d 影像编号 成像日期 空间基线距/m 时间基线距/d 1 2017-03-19 −34.87 −564 14 2019-04-02 −28.33 180 2 2017-04-12 −37.39 −540 15 2019-06-01 −23.04 240 3 2017-06-11 26.72 −480 16 2019-08-12 −78.11 312 4 2017-07-29 −40.10 −432 17 2019-10-11 53.56 372 5 2017-10-09 −33.23 −360 18 2019-12-10 87.43 432 6 2017-12-08 45.08 −300 19 2020-02-08 62.98 492 7 2018-02-06 −31.88 −240 20 2020-04-08 63.07 552 8 2018-04-07 12.50 −180 21 2020-05-14 −30.41 588 9 2018-06-06 −22.68 −120 22 2020-08-06 29.23 672 10 2018-08-05 −18.48 −60 23 2020-10-05 −33.29 732 11 2018-10-04 0.00 0 24 2020-12-04 23.03 792 12 2018-12-03 48.10 60 25 2021-04-03 5.72 912 13 2019-02-01 45.28 120 
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