Abstract
Identification and monitoring of unstable slopes across wide regions using Synthetic Aperture Radar Interferometry (InSAR) can further help to prevent and mitigate geological hazards. However, the low spatial density of measurement points (MPs) extracted using the traditional time-series InSAR method in topographically complex mountains and vegetation-covered slopes makes the final result unreliable. In this study, a method of time-series InSAR analysis using single- and multi-look phases were adopted to solve this problem, which exploited single- and multi-look phases to increase the number of MPs in the natural environment. Archived ascending and descending Sentinel-1 datasets covering Zhouqu County were processed. The results revealed that nine landslides could be quickly identified from the average phase rate maps using the Stacking method. Then, the time-series InSAR analysis with single- and multi-look phases could be used to effectively monitor the deformation of these landslides and to quantitatively analyze the magnitude and dynamic evolution of the deformation in various parts of the landslides. The reliability of the InSAR results was further verified by field investigations and Unmanned Aerial Vehicle (UAV) surveys. In addition, the precursory movements and causative factors of the recent Yahuokou landslide were analyzed in detail, and the application of the time-series InSAR method in landslide investigations was discussed and summarized. Therefore, this study has practical significance for early warning of landslides and risk mitigation.
Highlights
Landslides seriously threaten the safety of properties and lives [1,2,3,4], causing tens of billions of dollars in losses and more than 4300 fatalities around the world annually [5,6,7].Through the analysis of the characteristics of several landslides that caused heavy casualties and economic losses, it has been found that these landslides have the common characteristics of high position and concealment, which makes it difficult for geological field investigations to find these potential threats [8,9,10]
Based on the identified deformation regions, the topographic boundary was delimited, and the standard of delineation was along the ridge line where the deformation area is located, because landslides mostly occur in the area below the ridge line
The deformation rates of the landslides were inverted by time-series InSAR analysis with single- and multi-look phases
Summary
Landslides seriously threaten the safety of properties and lives [1,2,3,4], causing tens of billions of dollars in losses and more than 4300 fatalities around the world annually [5,6,7].Through the analysis of the characteristics of several landslides that caused heavy casualties and economic losses, it has been found that these landslides have the common characteristics of high position and concealment, which makes it difficult for geological field investigations to find these potential threats [8,9,10]. The identification and monitoring of deformation areas in topographically complex mountains and vegetation-covered slopes are significant for the prevention and mitigation of geological hazards. 2022, 14, 1026 landslide deformation analysis methods are mainly performed using field surveys, inclinometers, Global Positioning System (GPS), extensometers, total stations, and so on [15,16,17]. These methods cannot “blindly” monitor for landslides; that is, there needs to be knowledge of a landslide or, at minimum, a previously identified instability-prone area to establish monitoring, so they cannot identify and monitor landslides on a large scale Remote Sens. 2022, 14, 1026 landslide deformation analysis methods are mainly performed using field surveys, inclinometers, Global Positioning System (GPS), extensometers, total stations, and so on [15,16,17].
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