Volume 28 Issue 2
Apr.  2020
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Feng Wenkai, Dun Jiawei, Yi Xiaoyu, et al. 2020. Deformation analysis of Woda village old landslide in Jinsha river basin using SBAS-InSAR technology[J]. Journal of Engineering Geology, 28(2): 384-393. doi: 10.13544/j.cnki.jeg.2019-411
Citation: Feng Wenkai, Dun Jiawei, Yi Xiaoyu, et al. 2020. Deformation analysis of Woda village old landslide in Jinsha river basin using SBAS-InSAR technology[J]. Journal of Engineering Geology, 28(2): 384-393. doi: 10.13544/j.cnki.jeg.2019-411

DEFORMATION ANALYSIS OF WODA VILLAGE OLD LANDSLIDE IN JINSHA RIVER BASIN USING SBAS-INSAR TECHNOLOGY

doi: 10.13544/j.cnki.jeg.2019-411
Funds:

This study is supported by the National Natural Science Foundation of China 41977252

the Sichuan Provincial Youth Science and Technology Innovation Team Special Projects of China 2017TD0018

the Team Project of Independent Research of SKLGP SKLGP2016Z001

  • Received Date: 2019-10-08
  • Rev Recd Date: 2019-12-27
  • Publish Date: 2020-04-25
  • In recent years, unexpected high-level landslides have been increasing, resulting in adverse effects. This kind of geological hazard investigation is very difficult and concealed. It is difficult to solve the problem of disaster prevention and control by group survey and geological investigation alone. With the continuous improvement of the quality of radar remote sensing satellite data, the SBAS-InSAR technology in synthetic aperture Interferometric Radar(InSAR)provides a new technical approach for deformation detection of large-scale old landslides before disaster. The surface deformation of Wodacun landslide in Jinsha River Basin is monitored by SBAS-InSAR technology. The deformation results from March 30, 2017 to September 28, 2019 are obtained. Strong deformation area(Ⅰradar) and uniform deformation area(Ⅱradar) are delineated. The surface deformation rate, cumulative displacement trend and main crack deformation of the whole and local landslide in the revived area are analyzed. At the same time, the engineering geological survey and review are carried out on the spot. It is found that the resurrection and deformation signs of the old landslide are in good agreement with the interpretation results of the SBAS-InSAR technology. It is clear that the SBAS-InSAR technology has broad application prospects in the field of early warning and monitoring of geological disasters in complex mountain areas, and provides new ideas and references for monitoring and early warning similar to old landslides.
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  • Berardino P, Fornaro G, Lanari R, et al. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J].IEEE Transactions on Geoscience & Remote Sensing, 40(11): 2375-2383. http://cn.bing.com/academic/profile?id=9267c9b76553eb4232501bf4d2f123df&encoded=0&v=paper_preview&mkt=zh-cn
    Cascini L, Fornaro G, Peduto D. 2010. Advanced low-and full-resolution D-InSAR map generation for slow-moving landslide analysis at different scales[J].Engineering Geology, 112(1): 29-42. https://www.sciencedirect.com/science/article/abs/pii/S0013795210000049
    Casu F, Manzo M, Lanari R. 2000. A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from D-InSAR data[J].Remote Sensing of Environment, 102(3): 195-210. https://www.sciencedirect.com/science/article/pii/S0034425706000526
    Colesanti C, Wasowski J. 2006. Investigating landslides with space-borne Synthetic Aperture Radar(SAR)interferometry[J].Engineering Geology, 88(3): 173-199. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=76e04e80aa3b1d5c4a0e9e7422064125
    Dai K R, Zhuo G C, Xu Q, et al. 2019. Tracing the pre-failure two-dimensional surface displacements of Nanyu Landslide, Gansu province with radar interferometry[J].Geomatics and Information Science of Wuhan University, 44(12): 1778-1786. http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201912007
    Feng W K, Zhang G Q, Bai H L, et al. 2019. A preliminary analysis of the formation mechanism and development tendency of the huge Baige landslide in Jinshan River on October 11, 2018[J]. Journal of Engineering Geology, 27(2): 415-425.
    He X F, He M. 2012. InSAR earth observation data processing method and comprehensive measurement[M].Beijing: Science Press.
    Herrera G, Gutierrez F, Garcia-Davalillo J C, et al. 2013. Multi-sensor advanced DinSAR monitoring of very slow landslides: The Tena Valley case study(Central Spanish Pyrenees)[J]. Remote Sensing of Environment, 128(none): 31-43. http://cn.bing.com/academic/profile?id=e640af8be005cb07dd21f79ec3c05266&encoded=0&v=paper_preview&mkt=zh-cn
    Kang Y. 2016. Application of InSAR technology in landslide detection and monitoring in southwest mountainous areas[D].Xi'an: Chang'an University.
    Li L J, Yao X, Zhou Z K, et al. 2017. The deformation characteristics of a large landslide before and afire impoundment in the Xiluodu reservoir area based on InSAR technology[J].Journal of Engineering Geology, 25 (S1): 458-462.
    Liu X Y, Yang Z H, Guo C B, et al. 2017. Study of slow-moving landslide characteristics based on the SBAR-InSAR in the Xianshuihe fault zone[J].Geoscience, 31(5): 965-977. http://en.cnki.com.cn/Article_en/CJFDTotal-XDDZ201705008.htm
    Mo Y J, Wu Y, Liu X W. 2018. Monitoring the ground subsidence in Xiaojin County, Sichuan province based on small baseline subset technique[J].Engineering of Surveying and Mapping, 27(11): 46-50. http://d.old.wanfangdata.com.cn/Periodical/chgc201811009
    Nie B Q. 2018. Landslide deformation detection and identification based on InSAR technology——A case of Danba County[D]. Chengdu: Chengdu University of Technology.
    Tre altamira. 2017. Data in focus: precursor of Maoxian landslide measured from space[EB/OL].http://tre-altamira.com/news/data-focus-precursor-maoxian-landslide-measured-space/.2017-06-29.
    Wang J. 2018. Long-term spaceborne InSAR technology landslide geological disaster monitoring research[D].Beijing: Beijing Jiaotong University.
    Xu J Q, Ma T, Lu Y K, et al. 2019. Land subsidence monitoring in North Henan plain based on SBAS-InSAR technology[J].Journal of Jilin University(Earth Science Edition), 49(4): 1182-1191. http://d.old.wanfangdata.com.cn/Periodical/cckjdxxb201904025
    Xu Q, Li W L, Dong X J, et al. 2017. The Xinmocun landslide on June 24, 2017 in Maoxian, Sichuan: Characteristics and failure mechanism[J].Chinese Journal of Rock Mechanics and Engineering, 36(11): 2612-2628.
    Xu Q, Zheng G, Li W L, et al. 2018. Study on successive landslide damming events of Jinsha River in Baige Village on Octorber 11 and November 3, 2018[J]. Journal of Engineering Geology, 26(6): 1534-1551. http://d.old.wanfangdata.com.cn/Periodical/gcdzxb201806017
    Yu R. 2014. Xi'an County landslide monitoring research based on short baseline(SBAS)technology[D].Nanjing: Nanjing Normal University.
    Zhang J, Feng D X, Qi W, et al. 2018. Monitoring land subsidence in Panjin region with SBAS-InSAR method[J].Journal of Engineering Geology, 26(4): 999-1007. http://d.old.wanfangdata.com.cn/Periodical/gcdzxb201804024
    Zhang Y. 2018. Surface deformation monitoring based on InSAR technology and early identification of landslide[D].Lanzhou: Lanzhou University.
    Zhao C Y, Zhang Q, Zhang J. 2011. Deformation monitoring of ground fissure with SAR inter-ferometry in Qingxu, Shanxi province[J].Journal of Engineering Geology, 19(1): 70-75. http://en.cnki.com.cn/Article_en/CJFDTOTAL-GCDZ201101014.htm
    戴可人, 卓冠晨, 许强, 等. 2019.雷达干涉测量对甘肃南峪乡滑坡灾前二维形变追溯[J].武汉大学学报(信息科学版):44(12): 1778-1786. http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201912007
    冯文凯, 张国强, 白慧林, 等. 2019.金沙江"10 ·11"白格特大型滑坡形成机制及发展趋势初步分析[J].工程地质学报, 27(2): 415-425. doi: 10.13544/j.cnki.jeg.2018-392
    何秀凤, 何敏. 2012. InSAR对地观测数据处理方法与综合测量[M].北京:科学出版社.
    康亚. 2016. InSAR技术在西南山区滑坡探测与监测的应用[D].西安: 长安大学.
    李凌婧, 姚鑫, 周振凯, 等. 2017.溪洛渡库区某大型滑坡蓄水前后变形特征InAR分析[J].工程地质学报, 25 (S1): 458-462. doi: 10.13544/j.cnki.jeg.2017.s1.071
    刘筱怡, 杨志华, 郭长宝, 等. 2017.基于SBAS-InSAR的鲜水河断裂带蠕滑型滑坡特征研究[J].现代地质, 31(5): 965-977. doi: 10.3969/j.issn.1000-8527.2017.05.008
    莫玉娟, 吴洋, 刘学武. 2018.基于SBAS技术的四川阿坝州小金县地表形变监测[J].测绘工程, 27(11): 46-50. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=chgc201811009
    聂兵其. 2018.基于InSAR的滑坡形变探测及隐患识别研究——以丹巴县城区为例[D].成都: 成都理工大学.
    许军强, 马涛, 卢意恺, 等. 2019.基于SBAS-InSAR技术的豫北平原地面沉降监测[J].吉林大学学报(地球科学版), 49(4): 1182-1191. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=cckjdxxb201904025
    许强, 李为乐, 董秀军, 等. 2017.四川茂县叠溪镇新磨村滑坡特征与成因机制初步研究[J].岩石力学与工程学报, 36(11): 2612-2628. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=yslxygcxb201711002
    许强, 郑光, 李为乐, 等. 2018.2018年10月和11月金沙江白格两次滑坡—堰塞堵江事件分析研究[J].工程地质学报, 26(6): 1534-1551. doi: 10.13544/j.cnki.jeg.2018-406
    余睿. 2014.基于短基线(SBAS)技术的西和县滑坡监测研究[D].南京: 南京师范大学.
    张静, 冯东向, 綦巍, 等. 2018.基于SBAS-InSAR技术的盘锦地区地面沉降监测[J].工程地质学报, 26(4): 999-1007. doi: 10.13544/j.cnki.jeg.2017-382
    张毅, 2018基于InSAR技术的地表变形监测与滑坡早期识别研究[D].兰州: 兰州大学.
    赵超英, 张勤, 张静. 2011.山西清徐地裂缝形变的InSAR监测分析[J].工程地质学报, 19(1): 70-75. doi: 10.3969/j.issn.1004-9665.2011.01.011
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