Please wait a minute...
 
国土资源遥感  2020, Vol. 32 Issue (4): 16-22    DOI: 10.6046/gtzyyg.2020.04.03
  综述 本期目录 | 过刊浏览 | 高级检索 |
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
于海若1,2,3,4,5,6,7(), 宫辉力1,2,3,4,5,6,7(), 陈蓓蓓1,2,3,4,5,6,7, 周超凡1,2,3,4,5,6,7
1.首都师范大学水资源安全北京实验室,北京 100048
2.首都师范大学资源环境与地理信息系统北京市重点实验室,北京 100048
3.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
4.首都师范大学三维信息获取与应用教育部重点实验室,北京 100048
5.首都师范大学地面沉降机理与防控教育部重点实验室,北京 100048
6.首都师范大学资源环境与旅游学院,北京 100048
7.自然资源部京津冀平原地下水与面沉降野外科学观测研究站,北京 100048
Emerging risks and the prospect of urban underground space security based on InSAR-GRACE satellite under the new hydrological background
YU Hairuo1,2,3,4,5,6,7(), GONG Huili1,2,3,4,5,6,7(), CHEN Beibei1,2,3,4,5,6,7, ZHOU Chaofan1,2,3,4,5,6,7
1. Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
2. The Key Lab of Resource Environment and GIS of Beijing, Capital Normal University, Beijing 100048, China
3. Base of the State Key Laboratory of Urban Environmental Process and Digital Modeling, Capital Normal University, Beijing 100048, China
4. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
5. Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, Ministry of Education, Capital Normal University, Beijing 100048, China
6. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
7. Observation and Research Station of Groundwater and Land Subsidence in Beijing-Tianjin-Hebei Plain, Ministry of Natural Resources, Beijing 100048, China
全文: PDF(904 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

城市地下空间的开发利用引发的区域地面沉降是威胁京津冀城市群安全的重大灾害隐患。文章简要回顾了合成孔径雷达干涉测量(interferometric synthetic aperture Radar,InSAR)技术的发展历史,系统总结了重力恢复和气候实验(gravity recovery and climate experiment,GRACE)卫星在地下水储量应用方面取得的进展,阐述了制约沉降的多种因素最终归为地下空间多元场的思想。综合分析后认为,在南水北调-地下水开采相互作用的新水情背景下,InSAR和GRACE技术结合是研究地下空间演化对地面沉降影响的全新手段; 结合InSAR-GRACE技术,重新发现区域水循环规律,量化多元场对沉降演化的贡献,提出地下空间演化的地表响应研究框架,揭示地面沉降响应模式的形成机理,从而建立面向地下空间安全的新兴风险防控预警机制,实现对区域的科学调控。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
于海若
宫辉力
陈蓓蓓
周超凡
关键词 InSAR-GRACE地下空间演化地面沉降响应多元场相互作用调控机理    
Abstract

Regional surface subsidence caused by the development and use of urban underground space is a major hazard endangering the safety of Beijing-Tianjin-Hebei city cluster. This paper briefly reviews the development history of interferometic synthetic aperture Radar (InSAR) technology, systematically summarizes the progress of applying gravity recovery and climate experiment (GRACE) satellite in underground water reserve, illustrates multiple factors containing subsidence, and finally ascribes the subsidence to multiple fields of underground space. Under the new hydrological background of the interaction between South-to-North Water Diversion and mining of underground water, InSAR-GRACE technology is a brand-new means for studying the impact of underground space evolution on land subsidence. Based on InSAR-GRACE technology, this paper rediscovers the regional water circulation laws, quantifies the contribution of multiple fields to subsidence evolution, proposes the surface response research framework for the evolution of underground space, and reveals the formation mechanism on the surface subsidence response model, thereby establishing an emerging risks prevention and control early warning mechanism for underground space security and realizing scientific regulation and control of the region.

Key wordsInSAR-GRACE    underground space evolution    land subsidence response    multiple field interaction    regulation mechanism
收稿日期: 2019-12-12      出版日期: 2020-12-23
:  P237  
基金资助:国家自然科学基金重点项目“京津冀典型区地下空间演化与地面沉降响应机理研究”(41930109);国家自然科学基金重点项目“京津冀典型区地下空间演化与地面沉降响应机理研究”(D010702);国家自然科学基金面上项目“南水进京背景下地面沉降演化机理”(41771455);国家自然科学基金面上项目“南水进京背景下地面沉降演化机理”(D010702);北京卓越青年科学家项目(BJJWZYJH01201910028032);北京市自然基金项目“新水情背景下京津高铁沿线地面沉降演化机制及调控方法”(8182013);北京市优秀人才培养青年拔尖个人资助项目共同资助
通讯作者: 宫辉力
作者简介: 于海若(1991-),女,博士研究生,主要从事地图学与地理信息系统研究。Email:1284869155@qq.com
引用本文:   
于海若, 宫辉力, 陈蓓蓓, 周超凡. 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.
YU Hairuo, GONG Huili, CHEN Beibei, ZHOU Chaofan. Emerging risks and the prospect of urban underground space security based on InSAR-GRACE satellite under the new hydrological background. Remote Sensing for Land & Resources, 2020, 32(4): 16-22.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2020.04.03      或      https://www.gtzyyg.com/CN/Y2020/V32/I4/16
Fig.1  研究流程
[1] 自然资源部中国地质调查局. 三位一体监测网实时监控华北地面沉降[EB/OL].(2015-04-13)[2019-12-12]. http://www.cgs.gov.cn/xwl/cgkx/201603/t20160309_299270.html.
China Geological Survey Bureau,Ministry of Natural Resources. Real time monitoring of land subsidence in North China by Trinity monitoring network[EB/OL](2015-04-13)[2019-12-12]. http://www.cgs.gov.cn/xwl/cgkx/201603/t20160309_299270.html.
[2] Zhang Y Q, Gong H L, Gu Z Q, et al. Characterization of land subsidence induced by ground water withdraws in the plain of Beijing City,China[J]. Hydrogeology Journal, 2014,22(2):397-409
doi: 10.1007/s10040-013-1069-x
[3] Ferretti A, Prati C, Rocca F. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000,38(5):2202-2212.
[4] 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, 2003,40(11):2375-2383
[5] RémI M, Avouac J P, Taboury J. Measuring near field coseismic displacements from SAR images:Application to the Landers earthquake[J]. Geophysical Research Letters, 1999,26(19):3017-3020.
[6] Fialko Y A, Rubin A M. Thermal and mechanical aspects of magma emplacement in giant dike swarms[J]. Journal of Geophysical Research, 1999,104(b10):23033.
doi: 10.1029/1999JB900213
[7] Usai S. A least-squares approach for long-term monitoring of deformations with differential SAR interferometry[C]// Geoscience and Remote Sensing Symposium. IEEE, 2002.
[8] 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.
[9] Bechor N B D, Zebker H A. Measuring two-dimensional movements using a single InSAR pair[J]. Geophysical Research Letters, 2006,33(16):L16311.
[10] Zhang L, Lu Z, Ding X, et al. Mapping ground surface deformation using temporarily coherent point SAR interferometry:Application to Los Angeles Basin[J]. Remote Sensing of Environment, 2012,117(1):429-439.
[11] Ma P, Lin H. Robust detection of single and double persistent scatterers in urban built environments[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016,54(4):2124-2139.
[12] Wahr J, Molenaar M, Bryan F. Time variability of the Earth’s gravity field:Hydrological and oceanic effects and their possible detection using GRACE[J]. Journal of Geophysical Research Atmospheres, 1998,103(b12):30205-30229.
[13] Tapley B D, Bettadpur S, Ries J C, et al. GRACE measurements of mass variability in the earth system[J]. Science, 2004,305(5683):503-505.
pmid: 15273390
[14] Rodell M, Velicogna I, Famiglietti J S. Satellite based estimates of groundwater depletion in India[J]. Nature, 2009,460(7258):999-1002.
doi: 10.1038/nature08238 pmid: 19675570
[15] 张铁勤, 何祺胜, 荆琛琳, 等. 基于InSAR的北京市平原区地下水动态监测[J]. 科学技术与工程, 2019,19(12):16-22.
Zhang T Q, He Q S, Jing C L, et al. Dynamic monitoring of groundwater in the plain area of Beijing based on InSAR[J]. Science Technology and Engineering, 2019,19(12):16-22.
[16] 宫辉力, 李小娟, 潘云, 等. 京津冀地下水消耗与区域地面沉降演化规律[J]. 中国科学基金, 2017,31(1):72-77.
Gong H L, Li X J, Pan Y, et al. Groundwater depletion and regional land subsidence of the Beijing-Tianjin-Hebei area[J]. China Science Foundation, 2017,31(1):72-77.
[17] 程凌鹏, 范子训, 王新惠, 等. 南水进京后典型区域地下水与地面沉降新动态[J]. 人民黄河, 2018,40(7):82-87.
Cheng L P, Fan Z X, Wang X H, et al. New trend of groundwater and land subsidence in typical areas after the south-to-north water transfer into Beijing[J]. Yellow River, 2018,40(7):82-87.
[18] 王永立. 天津市中心城区地下空间资源评价[J]. 地球科学与环境学报, 2008,30(2):166-171.
Wang Y L. Evaluation of underground space resources in downtown Tianjin[J]. Journal of Geosciences and Environment, 2008,30(2):166-171.
[19] 李永树, 肖林萍. 地面沉降预测参数的变化规律与计算方法[J]. 西南交通大学学报, 2006,41(4):424-428.
Li Y S, Xiao L P. Change rule and calculation method of land subsidence prediction parameters[J]. Journal of Southwest Jiaotong University, 2006,41(4):424-428.
[20] 柳昆, 彭建, 彭芳乐. 地下空间资源开发利用适宜性评价模型[J]. 地下空间与工程学报, 2011,7(2):219-231.
Liu K, Peng J, Peng F L. Suitability evaluation model of underground space resources development and utilization[J]. Journal of Underground Space and Engineering, 2011,7(2):219-231.
[21] 刘健, 魏永耀, 高立. 苏州城市规划区地下空间开发适宜性评价[J]. 地质学刊, 2014,38(1):94-97.
Liu J, Wei Y Y, Gao L. Suitability evaluation of underground space development in Suzhou urban planning area[J]. Journal of Geology, 2014,38(1):94-97.
[22] 胡杨. 国际风险管理理事会(IRGC)2005年北京年会综述[J]. 中国软科学, 2005(10):157-160.
Hu Y. Summary of IRGC 2005 Beijing annual meeting[J]. China Soft Science, 2005(10):157-160.
[23] 王琳, 李迅, 包云轩, 等. 遥感技术在交通气象灾害监测中的应用进展[J]. 国土资源遥感, 2018,30(4):1-7.doi: 10.6046/gtzyyg.2018.04.01.
Wang L, Li X, Bao Y X, et al. Research progress of remote sensing application on transportation meteorological disasters[J]. Remote Sensing for Land and Resources, 2018,30(4):1-7.doi: 10.6046/gtzyyg.2018.04.01.
[1] 李梦梦, 范雪婷, 陈超, 李倩楠, 杨锦. 徐州矿区2016—2018年地面沉降监测与分析[J]. 自然资源遥感, 2021, 33(4): 43-54.
[2] 温银堂, 王铁柱, 王书涛, 王贵川, 刘诗瑜, 崔凯. 基于多尺度分割的高分辨率遥感影像镶嵌线自动提取[J]. 自然资源遥感, 2021, 33(4): 64-71.
[3] 赵晓晨, 吴皓楠, 李林宜, 孟令奎. 面向汛旱情监测的遥感影像GPU并行处理算法[J]. 自然资源遥感, 2021, 33(3): 107-113.
[4] 汪清川, 奚砚涛, 刘欣然, 周文, 徐欣冉. 生态服务价值对土地利用变化的时空响应研究——以徐州市为例[J]. 自然资源遥感, 2021, 33(3): 219-228.
[5] 郭文, 张荞. 基于注意力增强全卷积神经网络的高分卫星影像建筑物提取[J]. 国土资源遥感, 2021, 33(2): 100-107.
[6] 季民, 张超, 赵建伟, 严娟, 梁亮. 基于VCI指数的青藏地区春旱时空动态变化分析[J]. 国土资源遥感, 2021, 33(1): 152-157.
[7] 许赟, 许艾文. 基于随机森林的遥感影像云雪雾分类检测[J]. 国土资源遥感, 2021, 33(1): 96-101.
[8] 刘钊, 赵桐, 廖斐凡, 李帅, 李海洋. 基于语义分割网络的高分遥感影像城市建成区提取方法研究与对比分析[J]. 国土资源遥感, 2021, 33(1): 45-53.
[9] 周芳成, 唐世浩, 韩秀珍, 宋小宁, 曹广真. 云下遥感地表温度重构方法研究[J]. 国土资源遥感, 2021, 33(1): 78-85.
[10] 苏龙飞, 李振轩, 高飞, 余敏. 遥感影像水体提取研究综述[J]. 国土资源遥感, 2021, 33(1): 9-11.
[11] 张萌生, 杨树文, 贾鑫, 臧丽日. 一种基于格网索引优化的遥感影像自动配准算法[J]. 国土资源遥感, 2021, 33(1): 123-128.
[12] 张红利, 罗蔚然, 李艳. 基于粒子群优化和像元分解模型的遥感影像时空融合[J]. 国土资源遥感, 2020, 32(4): 33-40.
[13] 张玲, 刘斌, 葛大庆, 郭小方. 基于多源SAR数据唐山城区活动断裂微小差异形变探测[J]. 国土资源遥感, 2020, 32(3): 114-120.
[14] 高凯旋, 焦海明, 王新闯. 融合影像纹理、光谱与地形特征的森林冠顶高反演模型[J]. 国土资源遥感, 2020, 32(3): 63-70.
[15] 吴同, 彭玲, 胡媛. 基于SU-RetinaNet的高分辨率遥感影像非正规垃圾堆检测[J]. 国土资源遥感, 2020, 32(3): 90-97.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《自然资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 E-mail:zrzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发