Volume 9 Issue 3
Jun.  2020
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Article Navigation >  Journal of Radars  > 2020  >  9(3): 554-568
DAI Keren, TIE Yongbo, XU Qiang, et al. Early identification of potential landslide geohazards in alpine-canyon terrain based on SAR interferometry—a case study of the middle section of yalong river[J]. Journal of Radars, 2020, 9(3): 554–568. doi: 10.12000/JR20012
Citation: DAI Keren, TIE Yongbo, XU Qiang, et al. Early identification of potential landslide geohazards in alpine-canyon terrain based on SAR interferometry—a case study of the middle section of yalong river[J]. Journal of Radars, 2020, 9(3): 554–568. doi: 10.12000/JR20012
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Early Identification of Potential Landslide Geohazards in Alpine-canyon Terrain Based on SAR Interferometry—a Case Study of the Middle Section of Yalong River (in English)

doi: 10.12000/JR20012
  • 1.

    State Key Laboratory of Geohazard Prevention and Geoenviroment Protection, Chengdu University of Technology, Chengdu 610059, China

  • 2.

    College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China

  • 3.

    China Geological Survey Chengdu geological survey center, Chengdu 610081, China

Funds:  The Public Geological Survey Project of China Geological Survey (DD20190640), The National Natural Science Foundation of China (41801391), The Provincial Key R&D Program of the Sichuan Ministry of Science and Technology (2019YFS0074), Sichuan Science and Technology Plan Project (2019YJ0404), State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (SKLGP2018Z019)
More Information
  • Author Bio:

    DAI Keren was born in Sichuan, China in 1989. He is currently a professor and doctoral supervisor in Chengdu University of Technology and permanent researchers of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection. His main research interests include the early identification of landslide hazards in alpine-valley area by synthetic aperture radar interferometry and early warning, remote sensing landslide disaster assessment and cataloging, etc. In recent five years, he has published more than 10 papers in international remote sensing journals such as IEEE GRSM, RSE, INT J APPL EARTH OBS, etc. E-mail: daikeren17@cdut.edu.cn

    TIE Yongbo was born in Yunnan, China in 1979. He is currently a professor of engineer of Chengdu Geological Survey Center of China Geological Survey, doctoral supervisor, and candidate of the 12th academic leader in Sichuan province. His research direction is the formation mechanism and risk assessment of geological disasters. E-mail: tyb038@qq.com

    XU Qiang was born in Sichuan, China in 1968. He is currently a professor and doctoral supervisor, vice President of Chengdu University of Technology, Executive Vice Director of State Key Laboratory of Geohazard Prevention and Geoenvironment Protecion, winner of National Outstanding Youth Fund, Distinguished Professor of Cheungkong Scholars program of the Ministry of Education, National Outstanding professional Technology Talent, national May 1st labor Medal winner, the State Council special allowance experts. Specializing in the mechanism of geological hazards, early identification, monitoring and early warning and emergency response, the scientific research achievements completed as a core member won two national science and technology progress award, provincial and ministerial science and technology progress award, six prizes.E-mail: xq@cdut.edu.cn

    FENG Ye was born in Sichuan, China in 1992. He is now postgraduate student in Chengdu University of Technology. His main research fields are InSAR data processing and application. E-mail: 2018050049@stu.cdut.edu.cn

    ZHUO Guanchen was born in Fujian, China in 1995. He is now postgraduate student in Chengdu University of Technology. He is mainly engaged in surface deformation monitoring research based on synthetic aperture radar interferometry. E-mail: zhuoguanchenRS@foxmail.com

    SHI Xianlin was born in Sichuan, China in 1980. She is now Ph.D., associate professor, tutor for postgraduate students. Member of the Education Committee of the Society of Surveying, Mapping and Geographic Information of Sichuan province, won the second prize of Higher Education Teaching Achievement of Sichuan Province and the third prize of The Progress Award of Surveying, Mapping and Technology of Sichuan Province. Her research interests include remote sensing geology and space information intelligence services. E-mail: shixianlin06@cedut.edu.cn

  • Corresponding author: TIE Yongbo, tyb2009@qq.com; XU Qiang, xq@cdut.edu.cn
  • Received Date: 2020-03-01
  • Rev Recd Date: 2020-06-01
    • Available Online: 2020-06-19
  • Publish Date: 2020-06-01
    Abstract
  • Landslide disasters occur frequently in the western mountainous regions of China and are characterized by high concealment, suddenness, and strong destructiveness. Early identification of potential disaster hazards is the most effective prevention and mitigation measure. The western mountainous areas mostly have a wide range of alpine-canyon terrain, which is hard or even impossible to reach. Moreover, traditional early identification methods, such as manual inspection, are difficult to implement in these areas. As an emerging radar remote-sensing method, Interferometric Synthetic Aperture Radar (InSAR) can efficiently and accurately identify the hidden dangers of landslides. Based on the synthetic aperture radar data of the European Space Agency’s Sentinel-1, this study used time series InSAR technology to identify the potential landslide hazards in the alpine-canyon terrain along the Yajiang-Muli County of the Yalong River; eight potential geohazards were detected. On the basis of the historical data of landslide hazards and the interpretation of optical remote sensing data, the results of early identification were verified and analyzed, and the danger level of the disaster points was evaluated. The influence of geometric distortion in InSAR technology on the early identification of potential landslides in alpine-canyon terrain was also discussed. This case study can provide powerful data and technical support for local disaster prevention and mitigation and provide ideas and references for the early identification of the hidden dangers of landslides in mountain-valley areas.

     

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