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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:

第45卷

期数:

2023年第03期

页码:

578-589

栏目:

大地测量、遥感与地学大数据

出版日期:

2023-05-15

文章信息/Info

Title:

Identification and Deformation Monitoring of Unstable Slopes in Longyangxia Reservoir Area, the Upper Reach of Yellow River, China Based on Multi-temporal InSAR Technology

文章编号:

1672-6561(2023)03-0578-12

作者:

费新峰¹; 田 野²; 赵超英²; 3; 4*; 刘海敏¹; 陈恒祎²

(1. 国家电投集团青海黄河电力技术有限责任公司,青海 西宁 810003; 2. 长安大学 地质工程与测绘学院,陕西 西安 710054; 3. 长安大学 西部矿产资源与地质工程教育部重点实验室,陕西 西安 710054; 4. 长安大学 自然资源部生态地质与灾害防控重点实验室,陕西 西安 710054)

Author(s):

FEI Xin-feng¹;  TIAN Ye²;  ZHAO Chao-ying²; 3; 4*;  LIU Hai-min¹;  CHEN Heng-yi²

(1. State Power Investment Corporation Qinghai Yellow River Electric Power Technology Co., Ltd., Xining 810003, Qinghai, China; 2. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China; 3. Key Laboratory of Western China's Mineral Resources and Geological Engineering of Ministry of Education, Chang'an University, Xi'an 710054, Shaanxi, China; 4. Key Laboratory of Ecological Geology and Disaster Prevention of Ministry of Natural Resources, Chang'an University, Xi'an 710054, Shaanxi, China)

关键词:

边坡识别;  相干点目标分析方法;  DS-InSAR技术;  形变监测;  二维分解;  小波分析;  查纳滑坡;  黄河

Keywords:

slope identification;  IPTA method;  DS-InSAR technology;  deformation monitoring;  two-dimensional decomposition;  wavelet analysis;  Chana landslide;  Yellow River

分类号:

P237

DOI:

10.19814/j.jese.2022.11042

文献标志码:

A

摘要:

黄河上游龙羊峡水库的建设改变了两岸的水文地质条件,库区水位周期性升降引起的渗透和侵蚀导致库岸坍塌和滑坡局部变形,非常有必要开展不稳定边坡的识别与监测,为库区坡体失稳因素研究以及预警预报提供技术支撑。采用2015年1月至2021年8月升降轨Sentinel-1A SAR影像,基于相干点目标分析(IPTA)方法对龙羊峡库区边坡进行识别,共识别出15处不稳定边坡。其中,查纳滑坡历史上多次发生塌滑现象,现今仍处于活跃状态,对库区人民生命财产与大坝工程安全造成潜在威胁,为此对查纳滑坡开展重点监测。首先,采用DS-InSAR技术获取该滑坡升降轨雷达视线向(LOS)形变; 然后,结合升降轨形变结果进行二维时序形变分解; 最后,采用小波分析定量分析了地表时序形变反演结果与降雨量、库区水位变化的相关性。结果表明:DS-InSAR技术获取的形变场比相干点目标分析方法更加完整; 查纳滑坡东部坡体位移大于中部与西部坡体位移,且垂直向位移大于东西向位移; 查纳滑坡位移时间序列与降雨量序列相关性不高,降雨可能不会显著促进滑坡的位移; 滑坡位移与库区水位均具有很强的年度周期变化,并且滑坡位移时间序列滞后库区水位序列约半年。

Abstract:

The construction of Longyangxia reservoir on the upper reach of Yellow River has altered the hydrogeological conditions on both banks. Infiltration and erosion caused by the periodic rise and fall of the reservoir water level have led to the collapse of the reservoir banks and the local deformation of landslides. Therefore, it is necessary to identify and monitor the unstable slopes, in order to provide technical support for the study of slope instability factors as well as early warning and forecasting in the reservoir area. Both Sentinel-1A SAR images of the ascending and descending orbits from January 2015 to August 2021 were involved to identify the unstable slopes on the bank of Longyangxia reservoir based on interferometric point target analysis(IPTA)method, and 15 unstable slopes were identified. The Chana landslide, which has historically collapsed many times, is still active and poses a potential threat to people's lives and property in the reservoir area and the safety of the dam project, so key monitoring is carried out on the Chana landslide. For the Chana landslide, DS-InSAR technology was used to obtain the LOS deformation of SAR images of the ascending and descending orbits; then, the two-dimensional time series decomposition was carried out by combining the deformation inversion results of the ascending and descending orbits; finally, the wavelet analysis was used to quantitatively discuss the relationship of deformation inversion results of surface time series decomposition with the change of rainfall and reservoir water level. The results show that the deformation field obtained by DS-InSAR technology is more complete than that obtained by IPTA method; the deformation at the eastern section is larger than the one in the central and western section, and the vertical displacement is larger than the east-west displacement; the time series of Chana landslide displacement is not highly correlated with rainfall series, and rainfall may not significantly contribute to landslide displacement; both landslide displacement and reservoir water level have strong annual cycle changes, and the time series of landslide displacement lags reservoir water level series by about half a year.

参考文献/References:

[1] TIAN C C,TIAN H,LI C Y,et al.Stability Evaluation of Massive Landslides Using Ensembled Analysis of Time-series InSAR and Numerical Simulation Along the Yellow River,Northwestern of China[J].Geofluids,2022,2022:6546372.
[2] 吴其伟,李天池.半成岩大型滑坡机制和滑速分析[J].山地研究,1986,4(1):47-53.
WU Qi-wei,LI Tian-chi.Analyses of Formation Me-chanism and Sliding Velocity of Vast Landslides of Poorly Consolidated Rocks[J].Mountain Research,1986,4(1):47-53.
[3] 舒 宁.雷达影像干涉测量原理[M].武汉:武汉大学出版社,2003.
SHU Ning.Radar Image Interferometry Principle[M].Wuhan:Wuhan University Press,2003.
[4] WASOWSKI J,BOVENGA F.Investigating Landsli-des and Unstable Slopes with Satellite Multi Temporal Interferometry:Current Issues and Future Perspectives[J].Engineering Geology,2014,174:103-138.
[5] SHI X G,LIAO M S,LI M H,et al.Wide-area Landslide Deformation Mapping with Multi-path ALOS PALSAR Data Stacks:A Case Study of Three Gorges Area,China [J].Remote Sensing,2016,8(2):136.
[6] DONG J,ZHANG L,TANG M G,et al.Mapping Landslide Surface Displacements with Time Series SAR Interferometry by Combining Persistent and Dis-tributed Scatterers:A Case Study of Jiaju Landslide in Danba,China[J].Remote Sensing of Environment,2018,205:180-198.
[7] 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.
ZHU Jian-jun,LI Zhi-wei,HU Jun,et al.Research Progress and Methods of InSAR for Deformation Monitoring [J].Acta Geodaetica et Cartographica Sinica,2017,46(10):1717-1733.
[8] FERRETTI A,PRATI C,ROCCA F.Permanent Scat-terers in SAR Interferometry[J].IEEE Transactions on Geoscience and Remote Sensing,2001,39(1):8-20.
[9] 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.
[10] ZHAO C Y,KANG Y,ZHANG Q,et al.Landslide Identification and Monitoring Along the Jinsha River Catchment(Wudongde Reservoir Area),China,Using the InSAR Method[J].Remote Sensing,2018,10(7):993.
[11] 廖明生,董 杰,李梦华,等.雷达遥感滑坡隐患识别与形变监测[J].遥感学报,2021,25(1):332-341.
LIAO Ming-sheng,DONG Jie,LI Meng-hua,et al.Radar Remote Sensing for Potential Landslides Detection and Deformation Monitoring [J].National Remote Sensing Bulletin,2021,25(1):332-341.
[12] 赵超英,刘晓杰,张 勤,等.甘肃黑方台黄土滑坡InSAR识别、监测与失稳模式研究[J].武汉大学学报(信息科学版),2019,44(7):996-1007.
ZHAO Chao-ying,LIU Xiao-jie,ZHANG Qin,et al.Research on Loess Landslide Identification,Monitoring and Failure Mode with InSAR Technique in Heifangtai,Gansu[J].Geomatics and Information Science of Wuhan University,2019,44(7):996-1007.
[13] SHI X G,YANG C,ZHANG L,et al.Mapping and Characterizing Displacements of Active Loess Slopes Along the Upstream Yellow River with Multi-temporal InSAR Datasets[J].Science of the Total Environment,2019,674:200-210.
[14] 代 聪,李为乐,陆会燕,等.甘肃省舟曲县城周边活动滑坡InSAR探测[J].武汉大学学报(信息科学版),2021,46(7):994-1002.
DAI Cong,LI Wei-le,LU Hui-yan,et al.Active Landslides Detection in Zhouqu County,Gansu Province Using InSAR Technology[J].Geomatics and Information Science of Wuhan University,2021,46(7):994-1002.
[15] 吴绿川,王剑辉,符 彦.基于InSAR技术和光学遥感的贵州省滑坡早期识别与监测[J].测绘通报,2021(7):98-102.
WU Lu-chuan,WANG Jian-hui,FU Yan.Early Identifying and Monitoring Landslides in Guizhou Pro-vince with InSAR and Optical Remote Sensing[J].Bulletin of Surveying and Mapping,2021(7):98-102.
[16] SUN R R,ZHAO C Y.Karst Landslides Detection and Monitoring with Multiple SAR Data and Multi-dimensional SBAS Technique in Shuicheng,Guizhou,China[J].Frontiers in Earth Science,2023,11:383.
[17] CHEN H Y,ZHAO C Y,SUN R R,et al.Two-dimensional Deformation Monitoring of Karst Landslides in Zongling,China,with Multi-platform Distri-buted Scatterer InSAR Technique[J].Landslides,2022,19(7):1767-1777.
[18] YIN Y P,LIU X J,ZHAO C Y,et al.Multi-dimensional and Long-term Time Series Monitoring and Early Warning of Landslide Hazard with Improved Cross-platform SAR Offset Tracking Method[J].Science China:Technological Sciences,2022,65(8):1891-1912.
[19] LIU X J,ZHAO C Y,ZHANG Q,et al.Three-dimensional and Long-term Landslide Displacement Estimation by Fusing C- and L-band SAR Observations:A Case Study in Gongjue County,Tibet,China[J].Remote Sensing of Environment,2021,267:112745.
[20] CHEN L Q,ZHAO C Y,LI B,et al.Deformation Monitoring and Failure Mode Research of Mining-indu-ced Jianshanying Landslide in Karst Mountain Area,China with ALOS/PALSAR-2 Images[J].Landslides,2021,18(8):2739-2750.
[21] ZHAO C Y,LU Z,ZHANG Q,et al.Large-area Landslide Detection and Monitoring with ALOS/PALSAR Imagery Data over Northern California and Southern Oregon,USA[J].Remote Sensing of Environment,2012,124:348-359.
[22] SAMSONOV S,VAN DER KOOIJ M,TIAMPO K.A Simultaneous Inversion for Deformation Rates and Topographic Errors of D-InSAR Data Utilizing Linear Least Square Inversion Technique[J].Computers & Geosciences,2011,37(8):1083-1091.
[23] SEZEN C.A New Wavelet Combined Innovative Po-lygon Trend Analysis(W-IPTA)Approach for Investigating the Trends in the Streamflow Regime in the Konya Closed Basin,Turkey[J].Theoretical and Applied Climatology,2023,151(3/4):1523-1565.
[24] JOSHI M,KOTHYARI G C,KOTLIA B S.Landslide Detection in Kinnaur Valley,NW India Using PS-InSAR Technique[J].Physical Geography,2023,DOI:10.1080/02723646.2023.2202932.
[25] LI Y F,ZUO X Q,YANG F,et al.Effectiveness Eva-luation of DS-InSAR Method Fused PS Points in Surface Deformation Monitoring:A Case Study of Hongta District,Yuxi City,China[J].Geomatics,Natural Hazards and Risk,2023,14(1):256813714.
[26] ZHANG Z L,ZENG Q J,JIAO J.Deformations Monitoring in Complicated-surface Areas by Adaptive Distributed Scatterer InSAR Combined with Land Cover:Taking the Jiaju Landslide in Danba,China as an Example[J].ISPRS Journal of Photogrammetry and Remote Sensing,2022,186:102-122.
[27] WANG J,WANG C,XIE C,et al.Monitoring of Lar-ge-scale Landslides in Zongling,Guizhou,China,with Improved Distributed Scatterer Interferometric SAR Time Series Methods[J].Landslides,2020,17(8):1777-1795.
[28] WANG Y J,CUI X M,CHE Y H,et al.Automatic Identification of Slope Active Deformation Areas in the Zhouqu Region of China with DS-InSAR Results[J].Frontiers in Environmental Science,2022,10:883427.
[29] 徐源懋,武 震,刘 杰.基于SBAS-InSAR技术的舟曲县潜在滑坡灾害早期识别及降水相关性分析[J].工程科学与技术,2022,DOI:10.15961/j.jsuese.202200486.
XU Yuan-mao,WU Zhen,LIU Jie.Early Identification of Potential Landslide Hazards and Precipitation Correlation Analysis in Zhouqu County Based on SB-AS-InSAR Technology[J].Advanced Engineering Science,2022,DOI:10.15961/j.jsuese.202200486.
[30] 孔祥如.地层形变与地下水位分层监测数据的交叉小波分析[J].煤田地质与勘探,2022,50(6):138-146.
KONG Xiang-ru.Cross Wavelet Analysis Between Layered Monitoring Data of Stratum Deformation and Groundwater Level Regime [J].Coal Geology & Exploration,2022,50(6):138-146.
[31] LIU Y,QIU H J,YANG D D,et al.Deformation Responses of Landslides to Seasonal Rainfall Based on InSAR and Wavelet Analysis[J].Landslides,2022,19(1):199-210.
[32] WEN N,DAI K,TOMAS R,et al.Revealing the Ti-me Lag Between Slope Stability and Reservoir Water Fluctuation from InSAR Observations and Wavelet Tools:A Case Study in Maoergai Reservoir(China)[J].GIScience & Remote Sensing,2023,60(1):2565-93766.
[33] DONG J H,NIU R Q,LI B Q,et al.Potential Landslides Identification Based on Temporal and Spatial Filtering of SBAS-InSAR Results[J].Geomatics,Na-tural Hazards and Risk,2023,14(1):52-75.
[34] 闫 霈,张友静,张 元.利用增强型水体指数(EWI)和GIS去噪音技术提取半干旱地区水系信息的研究[J].遥感信息,2007,94(6):62-67.
YAN Pei,ZHANG You-jing,ZHANG Yuan.A Study on Information Extraction of Water System in Semi-arid Regions with the Enhanced Water Index(EWI)and GIS Based Noise Remove Techniques[J].Remote Sensing Information,2007,94(6):62-67.
[35] LI Y F,ZUO X Q,ZHU D M,et al.Identification and Analysis of Landslides in the Ahai Reservoir Area of the Jinsha River Basin Using a Combination of DS-InSAR,Optical Images,and Field Surveys[J].Remote Sensing,2022,14(24):6274.
[36] 吕加颖.基于时序InSAR技术的阿海库区滑坡体监测应用研究[D].昆明:昆明理工大学,2021.
LYU Jia-ying.Application Study on Landslide Monitoring in Ahai Reservoir Area Based on Time-series InSAR Technology[D].Kunming:Kunming Univer-sity of Science and Technology,2021.
[37] CENNI N,FIASCHI S,FABRIS M,et al.Integrated Use of Archival Aerial Photogrammetry,GNSS,and InSAR Data for the Monitoring of the Patigno Landslide(Northern Apennines,Italy)[J].Landslides,2021,18(6):2247-2263.
[38] HE Y,WANG W H,ZHANG L F,et al.An Identification Method of Potential Landslide Zones Using InSAR Data and Landslide Susceptibility[J].Geoma-tics,Natural Hazards and Risk,2023,14(1):257385979.
[39] YANG S,LI D Y,LIU Y J,et al.Landslide Identification in Human-modified Alpine and Canyon Area of the Niulan River Basin Based on SBAS-InSAR and Optical Images[J].Remote Sensing,2023,15(8):1998.

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备注/Memo

备注/Memo:

收稿日期:2022-11-12; 修回日期:2023-02-17
基金项目:国家自然科学基金项目(41929001); 国家重点研发计划项目(2022YFC3004302)
作者简介:费新峰(1971-),男,青海西宁人,高级工程师,E-mail:fxf13619780688@163.com。
*通讯作者:赵超英(1976-),男,山西平遥人,教授,博士研究生导师,工学博士,E-mail:cyzhao@chd.edu.cn。

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更新日期/Last Update: 2023-05-30