Potential landslides identification based on temporal and spatial filtering of SBAS-InSAR results

Abstract

Interferometric Synthetic Aperture Radar (InSAR) is an important method for acquiring surface deformation. Considering the difficulty of the identification work, the identification of landslides needs to be combined with the context of the pregnant disaster and the precipitating conditions. To identify potential landslides, we applied spatial and temporal filtering to the InSAR results, which consists of rainfall and landslide susceptibility mapping. In this paper, taking the Badong Ecological Barrier Zone of the Three Gorges reservoir area as the study area, the deformation aggregation areas in the study area were obtained by applying Small Baseline Subset InSAR (SBAS-InSAR) technology and spatial statistical analysis. We screened deformation aggregation areas by combining the susceptibility map and the correlation analysis of rainfall and deformation. Field verification and investigation were conducted on the suspected deformation areas, and 11 landslides were found to have signs of deformation, two of them are newly discovered landslides. In addition, we selected one of the landslides, the Songjiawuchang landslide, and compared the InSAR results with the GPS accumulated displacement to verify the reliability of the results. This research demonstrated the feasibility of combining InSAR results with spatial susceptibility maps and monthly rainfall factors for landslides identification methods.

Key policy highlights

• Applied Spatial filtering and temporal filtering on the InSAR results.

• Evaluated in conjunction with geological hazards themselves.

• Landslide identification accuracy significantly improved.

Keywords:

• Landslides identification
• SBAS-InSAR
• landslide susceptibility mapping
• Pearson correlation coefficient
• hot spot analysis
• Three Gorges Reservoir Area

Data availability statement

The data that support the findings of this study are available from the Hubei Geological Environment Station but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Hubei Geological Environment Station.

Additional information

Funding

This work was supported by the 2019 Central Natural Disaster Prevention and Control System Construction Grant (Regional Integrated Remote Sensing Monitoring and Hidden Danger Identification in Enshi Prefecture) (HBYM-GTJ-2020-GK-1002) and the Geohazard Prevention and Control in Three Gorges Follow-up Work – Guidance on Professional Monitoring Construction and Early Warning Analysis of Geohazards in Three Gorges Reservoir Area (Year 2022) (000121-2012A-C50-021).