Monitoring and forecasting analysis of a landslide in Xinmo, Mao County, using Sentinel-1 data

  • Author(s): Yuxin Liu, Caijun Xu, and Yang Liu
  • DOI: 10.3319/TAO.2018.10.16.01
  • Keywords: Maoxian InSAR Landslide Monitoring Forecast
  • Citation: Liu, Y., C. Xu, and Y. Liu, 2019: Monitoring and forecasting analysis of a landslide in Xinmo, Mao County, using Sentinel-1 data. Terr. Atmos. Ocean. Sci., 30, 85-96, doi: 10.3319/TAO.2018.10.16.01
  • Sentinel-1 data was collected to calculate the time series of deformation
  • The time series of deformation is consistent with the accelerated creep model
  • The failure time calculated by inverse-velocity is one day apart from the failure
Abstract

On 24 June 2017, an enormous landslide struck the village of Xinmo in Mao County, Sichuan Province. Synthetic aperture radar (SAR) images from the Sentinel-1 satellite are chosen to monitor the landslide using the small baseline set (SBAS) technology, following which the deformation time series are obtained for the source area and are found to be consistent with the accelerated creep model. The displacement time series before the landslide clearly show movement processes associated with transient creep, steady-state creep and tertiary creep. The main deformation area is ascertained by calculating the average displacement of 5 representative regions. Three-month time series before the landslide are selected to calculate the failure time of the landslide both separately and together using the inverse-velocity method. The results show that the time series of the main deformation area can fit a linear model of the inverse velocities better than those of the marginal area, and the forecasted time is closer to the actual failure time. The forecasted time calculated using the time series of three regions in main deformation area is June 25, which is only one day apart from the actual failure time.

 

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