以新水情下北京地区作为研究对象，用2019年12月24日至2021年8月27日的52景Sentinel-1数据，采用SBAS-InSAR技术提取地面沉降信息。详细分析了沉降区域的空间分布特征及典型地区沉降演化过程，根据危险性分区量化指标对地面沉降危险性进行了初步研究，结果表明：北京地区地面沉降空间分布呈现明显的不均匀、不规则、漏斗式的运动特征，形成4个明显的沉降漏斗区（通州沉降区、朝阳金盏沉降区、海淀稻香湖公园沉降区、大兴机场周边沉降区）。北京朝阳金盏和高安屯地区的地表形变速率较大，均超过了-120 mm/a。严重沉降区、较严重和一般沉降区主要位于4个沉降漏斗区，面积占比约6.2%，值得重点关注，其他区域地面沉降危险性较低。
Taking Beijing under the new water regime as the research object, 52 Sentinel-1 data from December 24, 2019 to August 27, 2021 were used to extract land subsidence information using SBAS-InSAR technology. A detailed analysis of the spatial distribution characteristics of subsidence areas and the evolution process of typical subsidence areas was conducted. Based on quantitative indicators of hazard zoning, the risk of land subsidence was preliminarily studied. The results indicated that the spatial distribution of land subsidence in Beijing showed obvious uneven, irregular, and funnel-shaped motion characteristics, forming four distinct subsidence funnel zones (Tongzhou subsidence zone, Chaoyang Jinzhan subsidence zone, Haidian Daoxianghu Park subsidence zone, and the surrounding subsidence zone of Daxing Airport). The surface deformation rates in Jinzhan and Gao'antun areas of Chaoyang, Beijing, are relatively high, both exceeding -120 mm/a. The severe subsidence zones, relatively severe zones, and general severe zones are mainly located in four subsidence funnel zones, accounting for about 6.2%, which is worthy of special attention. The risk of land subsidence in other areas is relatively low.
2023,44（3）: 168-176 收稿日期：2023-05-24
DOI：10.3969/j.issn.1003-3246.2023.03.024
基金项目：国家自然科学青年基金（项目编号：42004010）；中国地震台网中心青年基金（项目编号：QNJJ-202202）
作者简介：祝杰(1992-),男,硕士,工程师,主要从事InSAR和GNSS数据处理及应用分析工作。E-mail:zhujie@seis.ac.cn
参考文献：
常占强,宫辉力,张景发,等. D-InSAR与PS-InSAR的理论模型、技术特点及应用领域[J]. 河北师范大学学报(自然科学版),2008,32(1):113-116.
何庆成,叶晓滨,李志明,等. 我国地面沉降现状及防治战略设想[J]. 高校地质学报,2006,12(2):161-168.
雷坤超. 南水北调前后北京平原区地下水和地面沉降演变特征[J/OL]. 地质学报,2023:1-20.[2023-05-15].https://doi.org/10.19762/j.cnki.dizhixuebao.2023013.
李永生,张景发,李振洪,等. 利用短基线集干涉测量时序分析方法监测北京市地面沉降[J]. 武汉大学学报(信息科学版),2013,38(11):1 374-1 377.
王超,张红,刘智,等. 基于D-InSAR的1993-1995年苏州市地面沉降监测[J]. 地球物理学报,2002,45(Z1):244-253.
许强,董秀军,李为乐. 基于天-空-地一体化的重大地质灾害隐患早期识别与监测预警[J]. 武汉大学学报(信息科学版),2019,44(7):957-966.
杨艳,贾三满,王海刚. 北京平原区地面沉降现状及发展趋势分析[J]. 上海地质,2010,31(4):23-28.
杨艳. 京津冀区域地面沉降灾害防治思考[J]. 城市地质,2015,10(1):1-7.
于海若,宫辉力,陈蓓蓓,等. 新水情下利用InSAR-GRACE卫星的新兴风险预警与城市地下空间安全展望[J]. 国土资源遥感,2020,32(4):16-22.
张景发,郭庆十,龚利霞. 应用InSAR技术测量矿山沉降与变化分析——以河北武安矿区为例[J]. 地球信息科学,2008,10(5):651-657.
张永红,吴宏安,康永辉. 京津冀地区1992-2014年三阶段地面沉降InSAR监测[J]. 测绘学报,2016,45(9):1 050-1 058.
周朝栋,宫辉力,张有全,等. 北京平原区地面沉降PS-InSAR监测[J]. 遥感信息,2017,32(1):17-22.
Berardino P, Fornaro G, Lanari R, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11):2 375-2 383.
Chen M, Tomás R, Li Z H, et al. Imaging land subsidence induced by groundwater extraction in Beijing (China) using satellite radar interferometry[J]. Remote Sensing, 2016, 8(6):468.
Eineder M, Hubig M, Milcke B. Unwrapping large interferograms using the minimum cost flow algorithm[C]//IGARSS'98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings.Seattle, WA, USA:IEEE, 1998.
Gabriel A K, Goldstein R M, Zebker H A. Mapping small elevation changes over large areas:Differential radar interferometry[J]. Journal of Geophysical Research:Solid Earth, 1989, 94(B7):9 183-9 191.
Massonnet D, Rossi M, Carmona C, et al. The displacement field of the Landers earthquake mapped by radar interferometry[J]. Nature, 1993, 364(6433):138-142.
Wright T J, Parsons B E, Lu Z. Toward mapping surface deformation in three dimensions using InSAR[J]. Geophysical Research Letters, 2004, 31(1):L01607.
