4.6 Article

Preliminary Identification of Geological Hazards from Songpinggou to Feihong in Mao County along the Minjiang River Using SBAS-InSAR Technique Integrated Multiple Spatial Analysis Methods

Journal

SUSTAINABILITY
Volume 13, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/su13031017

Keywords

landslide and collapse identification; SBAS-InSAR; visibility analysis; kernel density analysis; field investigation

Funding

  1. National Key Research and Development Program of China [2017YFC1501004]
  2. National Nature Science Foundation of China [41807227]

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This study utilized SBAS-InSAR technology to monitor surface deformation in Maoxian County, Sichuan Province, and identified 26 disaster areas including 20 potential landslides and 6 potential collapses from 18 deformation clusters through hot spot and kernel density analyses.
Landslides and collapses are common geological hazards in mountainous areas, posing significant threats to the lives and property of residents. Therefore, early identification of disasters is of great significance for disaster prevention. In this study, we used Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology to process C-band Sentinel-1A images to monitor the surface deformation from Songpinggou to Feihong in Maoxian County, Sichuan Province. Visibility analysis was used to remove the influence of geometric distortion on the SAR images and retain deformation information in the visible area. Hot spot and kernel density analyses were performed on the deformation data, and 18 deformation clusters were obtained. Velocity and slope data were integrated, and 26 disaster areas were interpreted from the 18 deformation clusters, including 20 potential landslides and 6 potential collapses. A detailed field investigation indicated that potential landslides No. 6 and No. 8 had developed cracks and were severely damaged, with a high probability of occurrence. Potential collapse No. 22 had developed fissures, exposing a dangerous rock mass and posing significant threats to the lives and property of residents. This study shows that the proposed method that combines visibility analysis, InSAR deformation rates, and spatial analysis can quickly and accurately identify potential geological disasters and provide guidance for local disaster prevention and mitigation.

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