时序InSAR监测京雄城际铁路河北段地面沉降

doi:10.13474/j.cnki.11-2246.2022.0205

测绘通报 ›› 2022, Vol. 0 ›› Issue (7): 64-70.doi: 10.13474/j.cnki.11-2246.2022.0205

时序InSAR监测京雄城际铁路河北段地面沉降

葛鹏飞^1,2,3, 刘辉^1,2,3, 陈蜜^1,2,3, 李昱^1,2,3, 丁瑞力^1,2,3, 刘菲^1,2,3

1. 首都师范大学资源环境与旅游学院, 北京 100048;
2. 首都师范大学城市环境过程与数字模拟国家重点实验室培育基地, 北京 100048;
3. 首都师范大学水资源安全北京实验室, 北京 100048

收稿日期:2021-08-23 出版日期:2022-07-25 发布日期:2022-07-28
通讯作者: 刘辉。E-mail:huixyt@163.com
作者简介:葛鹏飞(1999—),男,硕士生,研究方向为InSAR形变监测。E-mail:1336196302@qq.com
基金资助:
国家重点研发计划(2017YFB0503803)

Monitoring land subsidence of Hebei section of Beijing-Xiong'an intercity railway by time-series InSAR

GE Pengfei^1,2,3, LIU Hui^1,2,3, CHEN Mi^1,2,3, LI Yu^1,2,3, DING Ruili^1,2,3, LIU Fei^1,2,3

1. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China;
2. State Key Laboratory Breeding Base for Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China;
3. Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China

Received:2021-08-23 Online:2022-07-25 Published:2022-07-28

摘要/Abstract

摘要： 本文以京雄城际铁路河北段固安站至雄安站沿线作为研究区,利用2018—2020年共34景Sentinel-1B影像,基于小基线集雷达干涉测量技术(SBAS-InSAR)获取京雄城际铁路河北段沿线的地面沉降时空分布信息,结合空间自相关分析方法,揭示研究区地面沉降的空间分布格局,并对沉降原因进行初步分析。研究结果表明,京雄城际铁路河北段沿线地面沉降发展由北向南存在一定的差异。北部年均沉降速率小于10 mm/a,南部沉降较为严重,最大年均沉降速率达-105.6 mm/a,且沿线西部年均沉降速率高于东部区域。通过分析影响因素得知,地面沉降量与地下水埋深值存在相关性,地下水埋深高的地区地面沉降量较高。同时结合研究区土地利用变化结果发现,城市化建设所产生的静载荷对京雄城际铁路沿线的地面沉降产生一定的影响。

关键词: 京雄城际铁路, 地面沉降, SBAS-InSAR, 莫兰指数

Abstract: In this paper, the spatial and temporal distribution of land subsidence along the Beijing-Xiong'an intercity railway (Hebei section), from Gu'an station to Xiong'an station, is obtained by using 34 Sentinel-1B images from 2018 to 2020 based on SBAS-InSAR technology. Then, the spatial autocorrelation analysis is used to understand the spatial distribution characteristics of land subsidence in the study area. Finally, the causes of subsidence are analyzed combined with the hydrological data. The results show that, the development of land subsidence along Hebei section of Beijing-Xiong'an intercity railway is different from north to south. The average annual settlement rate in the north is less than 10 mm/a, and the maximum annual settlement rate in the south is -105.6 mm/a, and the average annual settlement rate in the west is higher than that in the east. By analyzing the influencing factors, it can be concluded that there is a correlation between ground subsidence and groundwater depth, and the area with high groundwater depth has a higher ground subsidence. At the same time, combined with the results of land use change in the study area, it is found that the static load caused by urbanization has a certain impact on the land subsidence along the Beijing-Xiong'an intercity railway.

Key words: Beijing-Xiong'an intercity railway, land subsidence, SBAS-InSAR, Moran's index

中图分类号:

P208

葛鹏飞, 刘辉, 陈蜜, 李昱, 丁瑞力, 刘菲. 时序InSAR监测京雄城际铁路河北段地面沉降[J]. 测绘通报, 2022, 0(7): 64-70.

GE Pengfei, LIU Hui, CHEN Mi, LI Yu, DING Ruili, LIU Fei. Monitoring land subsidence of Hebei section of Beijing-Xiong'an intercity railway by time-series InSAR[J]. Bulletin of Surveying and Mapping, 2022, 0(7): 64-70.

参考文献

[1] 薛禹群,张云,叶淑君,等.中国地面沉降及其需要解决的几个问题[J].第四纪研究, 2003(6):585-593.
[2] GALLOWAY D L,HUDNUT K W,INGEBRITSEN S E,et al.Detection of aquifer system compaction and land subsidence usinginterferometric synthetic aperture radar,Antelope Valley,Mojave Desert,California[J].Water Resources Research,1998,34(10):2573-2585.
[3] CHEN M,TOMÁS R,L 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.
[4] ZHAO X X,CHEN B B,GONG H L,et al.Land subsidence along the Beijing-Tianjin intercity railway during the period of the South-to-North Water Diversion Project[J].International Journal of Remote Sensing,2020,41(12):4447-4469.
[5] 周玉营,陈蜜,宫辉力,等.基于时序InSAR的京津高铁北京段地面沉降监测[J].地球信息科学学报,2017,19(10):1393-1403.
[6] 朱旭,李政,冯海龙,等.京雄城际铁路地下水开采条件下无砟轨道路基沉降特性[J].铁道建筑,2019,59(12):89-94.
[7] 吴文坛,石建峰,覃业韬,等.基于CORS网的河北省2013-2018年区域沉降监测[J].城市勘测,2020(1):105-108.
[8] 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):2375-2383.
[9] LANARI R,MORA O,MANUNTA M,et al.A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(7):1377-1386.
[10] FERRETTI A,PRATI C,ROCCA F.Nonlinear subsidence rate estimationusing permanent scatterers in differential SAR interferometry[J].Geoscience&Remote Sensing IEEE Transactions on,2000,38(5):2202-2212.
[11] 张佳佳,高波,刘建康,等.基于SBAS-InSAR技术的川藏铁路澜沧江段滑坡隐患早期识别[J].现代地质,2021,35(1):64-73.
[12] 胡乐银,张景发,商晓青.SBAS-InSAR技术原理及其在地壳形变监测中的应用[J].地壳构造与地壳应力文集,2010(22):82-89.
[13] 羊远新,许文学.基于PS-InSAR和SBAS-InSAR技术的某机场沉降监测[J].工程勘察,2020,48(8):59-66.
[14] 袁悦,贾丽云,张绪教,等.基于SBAS-InSAR技术的海口地区地面沉降监测及机理分析[J].地理与地理信息科学,2020,36(5):56-64.
[15] 张良玉,李兴阳,王志超,等.基于Moran's I指数的京津冀地区PM_2.5空间自相关分析[J].四川环境,2021,40(2):52-59.
[16] MORAN P.The interpretation of statistical maps[J].Journal of the Royal Statistical Society,1948,10(2),1948:243-251.
[17] 孙一可,宫辉力,陈蓓蓓,等.综合莫兰指数和交叉小波的不均匀沉降量化分析[J].国土资源遥感,2020,32(2):186-195.
[18] 丁晓彤,余卓渊,宋海慧,等.基于信息熵的中国自然疫源性疾病分布特征研究[J].地球信息科学学报,2019,21(12):1877-1887.
[19] 程蕊,朱琳,周佳慧,等.北京潮白河冲洪积扇地面沉降时空异质性特征及驱动因素分析[J].吉林大学学报(地球科学版),2021,51(4):1182-1192.
[20] ANSELIN L.Local indicators of spatial association-LISA[J].Geographical Analysis,2010,27(2):93-115.

时序InSAR监测京雄城际铁路河北段地面沉降

Monitoring land subsidence of Hebei section of Beijing-Xiong'an intercity railway by time-series InSAR

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	兰进京, 曲逸穹, 都伟冰, 高鑫, 马丹丹, 郑岩超. 典型矿业城市地表形变遥感监测及沉降特征分析[J]. 测绘通报, 2022, 0(6): 98-103.
[2]	张家勇, 邹银先, 刘黔云, 张楠, 龚伟, 李康伦. 利用时序InSAR进行毕节市潜在滑坡识别与形变监测[J]. 测绘通报, 2022, 0(6): 121-124.
[3]	曾学宏, 赵义花. 利用SBAS-InSAR技术分析西宁市地面沉降监测及驱动因素[J]. 测绘通报, 2022, 0(6): 137-142.
[4]	张玉鹏, 张永红, 刘青豪. 利用GRACE数据进行京津冀地区地面沉降与地下水耦合分析[J]. 测绘通报, 2022, 0(5): 89-94,125.
[5]	李冰峰, 李更尔, 那静, 涂梨平, 范军林, 吴洋. 利用SBAS时序技术识别地热资源开采引起的地表形变[J]. 测绘通报, 2022, 0(2): 43-49.
[6]	黄佳宾, 郭云开, 罗伟茂. 利用Sentinel-1监测武汉市地面沉降[J]. 测绘通报, 2021, 0(9): 53-58.
[7]	章诗芳, 张锦. 卡尔曼滤波在山西省西山煤田地面沉降GNSS监测中的应用[J]. 测绘通报, 2021, 0(9): 103-107.
[8]	王建业, 梁小龙, 金喜, 白泽朝, 齐二恒. 黄土填方区地表沉降时序InSAR监测分析[J]. 测绘通报, 2021, 0(8): 158-161.
[9]	翁昌凯, 肖添. SBAS技术支持下的临沧市地表时序形变分析[J]. 测绘通报, 2021, 0(7): 81-85.
[10]	黄俊松, 张春有, 王剑辉. 利用时序InSAR技术监测嵩明县地表形变[J]. 测绘通报, 2021, 0(7): 103-106,116.
[11]	翁昌凯, 朱习朋. 基于哨兵数据的云南地表形变监测[J]. 测绘通报, 2021, 0(6): 61-66,92.
[12]	祝昕刚, 李更尔. 利用多传感器SAR数据集监测城市地面沉降[J]. 测绘通报, 2021, 0(6): 71-75.
[13]	任文静, 贾洪果, 闫斌. SBAS-InSAR方法支持下的矿区地表沉降监测及参数反演[J]. 测绘通报, 2021, 0(3): 113-117,155.
[14]	曹发伟, 廖维谷. SBAS技术在矿区地面沉降监测中的应用[J]. 测绘通报, 2021, 0(3): 156-158,163.
[15]	朱邦彦, 任志忠, 张琪, 李云, 王晓. 利用SBAS-InSAR技术反演雅鲁藏布江色东普流域灾前冰川形变[J]. 测绘通报, 2021, 0(11): 31-35.