联合InSAR技术和地质数据反演普宁城区的地表沉降特征

doi:10.13474/j.cnki.11-2246.2021.0181

摘要/Abstract

摘要： 地表沉降是全球性的地质灾害之一，地表的迅速沉降会导致地表塌陷，从而破坏地下管道及地表建筑，最后造成巨大的经济损失甚至人员伤亡。我国地下工程及地表建筑扩建规模较大，这种地质灾害问题尤为突出。目前，监测地表形变的方法有很多，如水准测量、GPS、InSAR技术等。但通常情况下这些技术只能对地表的高程变化进行定量分析，而无法寻找灾害发生的诱因，缺少对地表沉降时空特征的定性分析。本文以广东普宁地区为例，将InSAR技术与该地区的水文地质特征相结合，从而实现对地表沉降监测从数据采集、处理到成因分析的整个流程的把控。InSAR技术可以验证地质特征的合理性，而地质特征又可以对监测范围及监测周期进行更科学的指导。本文通过这种分析方法，既调查出普宁城区的沉降区域，又对其背后成因进行了系统性的分析，为后续的防治措施及国土空间规划提供了更科学的指导。

关键词: 地表沉降, InSAR技术, 地质特征, 普宁市

Abstract: Surface subsidence is one of the global geological hazards problems. Rapid subsidence of the ground can lead to surface collapse, which can damage underground pipelines as well as surface buildings and eventually cause huge economic losses and even casualties. This geological hazards problem is particularly acute in China, where underground projects and surface buildings are undergoing massive expansion. There are many methods to monitor the surface deformation, such as level measurement, GPS, InSAR technology and so on. However, usually these techniques can only quantitatively analyze the elevation change of the ground surface, but cannot find out the causative factors for the occurrence of disasters, and lack qualitative analysis of the spatial and temporal characteristics of the ground settlement. In this paper, the InSAR technology is combined with the hydrogeology characteristics of the area. It takes the Puning area in Guangdong as an example, to realize the whole process of surface subsidence monitoring from data acquisition and processing to the analysis of the causes. In this paper, this analysis method not only investigates the subsidence area in the Puning city area, but also provides a systematic analysis of the causes behind it, which provides a more scientific guidance for the subsequent prevention and control measures.

Key words: surface subsidence, InSAR technology, geological characteristics, Puning city

中图分类号:

P237

李冰峰, 杨映新, 王冬凯, 伍玉金, 张志友. 联合InSAR技术和地质数据反演普宁城区的地表沉降特征[J]. 测绘通报, 2021, 0(6): 83-88.

LI Bingfeng, YANG Yingxin, WANG Dongkai, WU Yujin, ZHANG Zhiyou. Joint InSAR technology and geological data to inverse the surface subsidence characteristics of Puning city[J]. Bulletin of Surveying and Mapping, 2021, 0(6): 83-88.

参考文献

[1] 闫满存,李华梅,王光谦.广东沿海陆地地质环境质量定量评价研究[J].工程地质学报,2000,8(4):416-425.
[2] 张建国,魏平新.广东省主要地质灾害发育特点与防治对策[J].中国地质灾害与防治学报,2003,14(4):47-51.
[3] 独知行,阳凡林,刘国林,等.GPS与InSAR数据融合在矿山开采沉陷形变监测中的应用探讨[J].测绘科学,2007,32(1):55-57.
[4] 陈玉冬,李德平,高海丽,等.洞庭盆地东部地表垂直形变空间分布及原因分析[J].长江流域资源与环境,2014,23(S1):14-20.
[5] 朱建军,李志伟,胡俊.InSAR变形监测方法与研究进展[J].测绘学报,2017,46(10):1717-1733.
[6] 姚鑫,张路青,李凌婧,等.工程场址区域地壳稳定性InSAR评价研究[J].工程地质学报,2021,29(1):104-115.
[7] 李珊珊,李志伟,胡俊,等.SBAS-InSAR技术监测青藏高原季节性冻土形变[J].地球物理学报,2013,56(5):1476-1486.
[8] 詹景祥,千喜俊,闫成龙.利用SBAS技术监测洛杉矶地区地表形变[J].测绘工程,2018,27(6):45-49.
[9] 张丽玲,黄卫.影响普宁市热带气旋的气候特征[J].广东气象,2010,32(5):26-28.
[10] 朱建军,杨泽发,李志伟.InSAR矿区地表三维形变监测与预计研究进展[J].测绘学报,2019,48(2):135-144.
[11] 尹宏杰,朱建军,李志伟,等.基于SBAS的矿区形变监测研究[J].测绘学报,2011,40(1):52-58.
[12] 李政,崔帅,王江涛,等.InSAR应用中相位解缠算法的快速选取[J].测绘标准化,2017,33(4):33-37.
[13] 王宏宇,张庆涛,刘杰,等.利用短基线集技术监测地表形变[J].测绘科学,2015,40(10):123-127.
[14] 孙晓鹏,鲁小丫,文学虎,等.基于SBAS-InSAR的成都平原地面沉降监测[J].国土资源遥感,2016,28(3):123-129.
[15] 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(1):82-89.
[16] 汪啸. 广东沿海典型深大断裂带地热水系统形成条件及水文地球化学特征[D].武汉:中国地质大学,2018.
[17] 林本海,杨树庄,朱伯善,等.广东省地质构造与岩土工程基本特征[J].岩石力学与工程学报,2006,25(S2):3337-3346.
[18] 杨礼聪.潮汕经济区汕头片区的地表水和地下水的污染程度[J].城市建设理论研究(电子版),2016(30):36-38.
[19] 曹洪,孙子钧,李俊,等.潮州城区浸没影响的预测与实测资料分析[J].岩石力学与工程学报,2009,28(11):2161-2166.
[20] 施凤春,唐仲华,陈育斌,等.粤东典型区地面沉降时空演化特征及成因分析[J].安全与环境工程,2019,26(5):8-16.