Abstract
Landslides are a common natural hazard that causes casualties and unprecedented economic losses every year, especially in vulnerable developing countries. Considering the high cost of in-situ monitoring equipment and the sparse coverage of monitoring points, the Sentinel-1 images and Interferometric Synthetic Aperture Radar (InSAR) technique were used to conduct landslide monitoring and analysis. The Muyubao landslide in the Three Gorges Reservoir area in China was taken as a case study. A total of 37 images from March 2016 to September 2017 were collected, and the displacement time series were extracted using the Stanford Method for Persistent Scatterer (StaMPS) small baselines subset method. The comparison to global positioning system monitoring results indicated that the InSAR processing of the Muyubao landslide was accurate and reliable. Combined with the field investigation, the deformation evolution and its response to triggering factors were analyzed. During this monitoring period, the creeping process of the Muyubao landslide showed obvious spatiotemporal deformation differences. The changes in the reservoir water level were the trigger of the Muyubao landslide, and its deformation mainly occurred during the fluctuation period and high-water level period of the reservoir.
Highlights
Landslides are one of the most common types of natural hazards that cause serious economic losses, casualties, and damages to buildings, critical infrastructures and industrial settlements [1]
Traditional deformation monitoring equipment, such as an inclinometer, global positioning system (GPS), etc., are well-suitable, but their high costs limit their applications in underdeveloped areas
This study aims to explore the feasibility and effectiveness of Sentinel-1 images and Interferometric Synthetic Aperture Radar (InSAR) technique in landslide monitoring and analysis in the Three Gorges Reservoir area (TGRA) as a case example from an underdeveloped landslide-prone region
Summary
Landslides are one of the most common types of natural hazards that cause serious economic losses, casualties, and damages to buildings, critical infrastructures and industrial settlements [1]. Monitoring and early warning systems are effective methods to reduce the risk of landslides [3], but the application of them on each single, potentially unstable slope is often impossible in mountain areas, due to the high spatial frequency of affected slopes In such cases, remote sensing may help to reduce the cost and time for the application of mitigation measures, because it can provide a preliminary low-cost assessment of the severity of the slope instability and allow for the prioritization of critical cases. Among all the physical manifestations of a mass movement, the surface deformation is the most intuitive and comprehensive to measure and use for hazard assessment It is a critical indicator for developing landslide early warning systems. This study aims to explore the feasibility and effectiveness of Sentinel-1 images and InSAR technique in landslide monitoring and analysis in the TGRA as a case example from an underdeveloped landslide-prone region
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