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Volume 50 Issue 2
Mar.  2023
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YIN Yuling, XU Suning, WANG Jun, et al. Identification and time series monitoring of hidden dangers of geological hazards in the typical loess hilly regions[J]. Hydrogeology & Engineering Geology, 2023, 50(2): 141-149. DOI: 10.16030/j.cnki.issn.1000-3665.202211004
Citation: YIN Yuling, XU Suning, WANG Jun, et al. Identification and time series monitoring of hidden dangers of geological hazards in the typical loess hilly regions[J]. Hydrogeology & Engineering Geology, 2023, 50(2): 141-149. DOI: 10.16030/j.cnki.issn.1000-3665.202211004
shu

Identification and time series monitoring of hidden dangers of geological hazards in the typical loess hilly regions

  • 1.

    School of Ocean Sciences, China University of Geosciences （Beijing）, Beijing　100083, China

  • 2.

    Land Satellite Application Center, Ministry of Natural Resources, Beijing　100048, China

  • 3.

    Mineral Geological Survey Institute of Ningxia Huizu Zizhiqu, Yinchuan, Ningxia　750021, China

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  • Received Date: October 31, 2022
  • Revised Date: January 03, 2023
  • Accepted Date: January 28, 2023
  • Available Online: January 30, 2023
    Graphical Abstract
    • Abstract

  • The geomorphology of southern Ningxia is dominated by loess hills, with gullies and well-developed small landslides in the area, making surface deformation monitoring difficult. To explore the identification method of geological hazards in the loess hilly area, Jingyuan district in the city of Guyuan in Ningxia Huizu Zizhiqu is taken as the study area, and the SBAS-InSAR technology is applied to process a total of 11 periods of ascending L-band ALOS-2 data collected from July 2016 to May 2021 to obtain the deformation rate of the Jingyuan district. Combined with high-resolution optical images, a comprehensive analysis is carried out according to factors such as deformation rate, deformation scale, slope, and disaster-bearing body. A total of 27 suspected hidden dangers are identified. After field verification, 22 of them show obvious signs of deformation and have clear hazard-bearing bodies. The time-series deformation analysis of the typical hidden danger points shows that these areas have continuous and significant surface deformation during the monitoring period, and the maximum subsidence rate reaches 91.53 mm/a. The results show that the combined L-band SAR and high-definition optical image data and the application of the integrated remote sensing identification method are highly accurate and are of high applicability in the area. The next step is to collect L-band data on a combination of ascending and descending orbits and to conduct in-depth research on the basis of LiDAR data from drones in order to further improve the accuracy of geological hazard identification and to provide technical support for the precise prevention and control of geological hazards.

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