A multi-sensor approach to monitor slope displacement

Abstract:

The use of remote sensing toward slope monitoring and landslide detection has been widespread. Common techniques include interferometric synthetic aperture radar (InSAR), light detection and ranging (LiDAR) and optical photogrammetric methods. Each technique can measure ground motion when data over the same region are acquired through multiple acquisitions, with typical data outputs displayed in spatial form (e.g., displacement/velocity maps or two- and three-dimensional change detection models) or in temporal form (e.g., displacement time series).

The authors apply a multi-sensor approach - combining satellite-based InSAR, terrestrial LiDAR, and aerial optical photogrammetry - in order to optimize these remote sensing techniques based on their advantages and limitations. This application is conducted over a railroad corridor in southeastern Nevada. InSAR results include the calculation of displacement rates across many slopes over a long period of time. Two slopes, identified as potentially hazardous, are further analyzed in greater detail using LiDAR and optical photogrammetry. Slope displacements are measured using a point-cloud change detection analysis; the potential for stacking acquisitions to create displacement time-series is also explored. Overall, the goal is to illustrate the benefits of using a multi-sensor, remote sensing approach towards the monitoring of slope instability.