Abstract
We present a workflow for investigating large, slow-moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post-processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five-year windows, 2010–2015 and 2015–2020. Then, we perform post-processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST-derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations.
Highlights
The risk associated with landslides and slope instability has increased over the past several decades due to expanded development of mountainous areas to accommodate population and tourism growth [1] as well as increased frequency of extreme weather events resulting from ongoing climate change [2,3]
We present a procedure that exploits the deformation fields extracted by speckle tracking (ST) algorithms from multi-geometry datasets to characterize the progressive deformation that occurs in slopes affected by slow, very slow, and extremely slow landslides over a
The workflow presented in this paper combines ST and airborne laser scanning (ALS) techniques to enhance the interpretation of deformation and failure mechanisms of unstable rock slopes
Summary
The risk associated with landslides and slope instability has increased over the past several decades due to expanded development of mountainous areas to accommodate population and tourism growth [1] as well as increased frequency of extreme weather events resulting from ongoing climate change [2,3]. Among the most studied examples of landslides that use these integrated datasets are Downie Slide and Frank Slide in Canada [7,8,9,10], Aknes rockslide in Norway [11,12], Ruinon landslide in Italy [4,13], and the Randa rockslides in Switzerland [14,15] These examples are readily accessible for such integrated studies, but many other unstable slopes are located in remote areas with limited accessibility and a lack of detailed historical and surface and subsurface geological data.
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