Volume 44 Issue 7
Jul.  2019
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ZHAO Chaoying, LIU Xiaojie, ZHANG Qin, PENG Jianbing, XU Qiang. 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. DOI: 10.13203/j.whugis20190072
Citation: ZHAO Chaoying, LIU Xiaojie, ZHANG Qin, PENG Jianbing, XU Qiang. 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. DOI: 10.13203/j.whugis20190072
shu

Research on Loess Landslide Identification, Monitoring and Failure Mode with InSAR Technique in Heifangtai, Gansu

  • 1.

    School of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China

  • 2.

    State Key Laboratory of Geo-information Engineering, Xi'an 710054, China

  • 3.

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

Funds: 

The National Key Research and Development Program of China 2018YFC1504805

the National Natural Science Foundation of China 41731066

the National Natural Science Foundation of China 41874005

More Information
  • Author Bio:

    ZHAO Chaoying, PhD, professor, specializes in geodetic processing, SAR interferometry and geohazards monitoring. E-mail: zhaochaoying@163.com

  • Received Date: February 27, 2019
  • Published Date: July 04, 2019
    Graphical Abstract
    • Abstract
  • The interferometric synthetic aperture radar (InSAR) technique is used over Heifangtai loess terrace, Gansu province of China to map the distribution of potential loess landslides, the evolution of landslide deformation and the failure mode. Firstly, the archived synthetic aperture radar (SAR) datasets with different spatial resolutions and wavelengths from December 2006 to November 2017 are used to identify the potential landslides. Tens potential landslide areas are identified from December 2006 to March 2011 and from January 2016 to November 2016. Field investigation and optical remote sensing images validate the reliability and accuracy of the identified landslides. Then, the TerraSAR-X data with high spatial and temporal resolution are used to monitor the time series deformation of the typical unstable slopes. Results demonstrate that the landslides with the large accumulative deformation all occur in the following time, and the acceleration dates of failed landslides are successfully captured by InSAR time series results. Finally, two-dimensional deformation monitoring of loess landslide is conducted by combining with ascending and descending SAR datasets. The landslide failure mode are analyzed in depth according to the obtained two-dimensional deformation results, topographic map and remote sensing images. The accuracy of the obtained result is verified by field investigation.
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    • References (21)
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