流域库岸地质灾害的监测具有十分重要的意义,传统的地质灾害监测手段主要通过埋设内外观传感器进行监测,这种方式难以获取大范围的监测信息,且系统运行成本和维护成本较高。InSAR技术可以快速获取大范围、高精度的形变监测信息,面向西南某流域沿岸地质灾害监测的实际需求,选用ALOS PALSAR2星载合成孔径雷达影像数据,充分利用L波段对植被冠层的穿透性,对多植被库岸边坡进行基于InSAR技术的大面积普查。同时,利用GNSS设备,对普查获取的高危坡体进行重点监测,利用GNSS的监测数据对InSAR监测结果进行验证,根据监测结果显示,基于L波段的星载InSAR监测技术能够用于多植被库岸边坡的地质灾害监测中。基于星载InSAR形变监测技术,结合GNSS地面监测技术,打造形成“星-地”一体化的流域库岸监测体系,能够实时、精准提供监测数据信息,对选取安全的移民安置点、保障水利工程安全运行具有重要的实际意义,也是解决流域库岸灾害预警问题的一种崭新途径。
Abstract
It is of great significance to monitor the geological hazards along the river basin and reservoir banks. The traditional geological hazards monitoring means mainly monitor by embedding the internal and external sensors, which is difficult to obtain a large range of monitoring information, and the cost of system operation and maintenance is high. InSAR technology can quickly obtain deformation monitoring information with large range and high precision. Facing the actual needs of geological disaster monitoring along the water conservancy project in southwest China, ALOS PALSAR2 spaceborne synthetic aperture radar image data is used to make full use of the L-band penetrability of the vegetation canopy to conduct a large-scale census based on the InSAR technology on the slopes of multiple vegetation banks in this paper. At the same time, GNSS equipment is used to carry out focused monitoring of high-risk slopes obtained from the census, and GNSS monitoring results are used to verify InSAR monitoring results. According to the experimental results, the L-band spaceborne InSAR monitoring technology can be used for geological hazard monitoring of bank slopes of multi-generational banks. This paper is based on InSAR monitoring technology, combining GNSS ground monitoring technology, building from the “star-ground” integration of river bank monitoring system, can provide monitoring data in real time and accuracy, has important practical significance for ensuring the safe operation of hydraulic engineering. It is also a new way to solve the problem of disaster warning.
关键词
库岸边坡 /
地质灾害监测 /
合成孔径雷达干涉测量 /
全球卫星导航系统
{{custom_keyword}} /
Key words
bank reservoir /
geological disaster /
InSAR /
GNSS
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1]宋丹青,梁收运,王志强.库水位对库岸边坡稳定性的影响[J].人民黄河,2016,38(7):95-99.
[2]黄会宝,江德军,乔蓓.某水电站库岸边坡变形监测工作基点稳定性分析[J].水电能源科学,2016,34(9):71-75.
[3]曾光辉,刘吉春,喻胜虎,等.皂市库区泥坝溪滑坡治理方案设计实例[J].资源环境与工程,2009,23(5):633-636.
[4]刘广润,徐开祥.三峡水库沿岸移民区地质灾害防治研究[J].中国地质灾害与防治学报,2003(4):4-7.
[5]郑轩,邹从烈,高润德,等.三峡库区猴子石滑坡治理工程设计及实施综述[J].人民长江,2016,47(6):73-77,86.
[6]邹从烈,郑轩,熊传义,等.三峡库区猴子石滑坡防治工程设计[J].人民长江,2008(6):57-61,103,111.
[7]原中华人民共和国国土资源部, 全国地质灾害通报[N]. 2010-2016.
[8]WANG T, PERISSON D, LIAO M S, et al. Deformation monitoring by long term D-InSAR analysis in three gorges area, China[J]. IEEE International Geoscience and Remote Sensing Symposium, 2008,4:5-8.
[9]廖明生, 唐婧, 王腾, 等. 高分辨率SAR数据在三峡库区滑坡监测中的应用[J]. 中国科学: 地球科学, 2012,42(2):217-229.
[10]BERARDINO P, FORNARO G, LANARIR, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms [J]. Geoscience & Remote Sensing IEEE Transactions, 2002,40(11):2 375-2 383.
[11]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):2 202-2 212.
[12]FERRATTI A, SAVIO G, BARZAGHI R, et al. Submillimeter accuracy of InSAR time series: Experimental validation [J]. IEEE Transactions on Geoscience and Remote Sensing, 2007,45(5):1 142-1 153.
[13]田馨, 廖明生. InSAR技术在监测形变中的干涉条件分析[J]. 地球物理学报, 2013,56(3):812-823.
[14]ZHANG P, ZHAO Z. Evaluation of data applicability for D-InSAR in areas covered by abundant vegetation [J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences(ISPRS), 2018, Volume XLII-3:2 277-2 281.
[15]DONG J, ZHANG L, LI M H. Measuring precursory movements of the recent Xinmo landslide in Mao County, China with Sentinel-1and ALOS-PALSAR 2 PALSAR-2 datasets [J]. Landslides, 2018,15(1):135-144.