Inferring the Subsurface Geometry and Strength of Slow-moving Landslides
using 3D Velocity Measurements from the NASA/JPL UAVSAR
Abstract
The hazardous impact and erosive potential of slow-moving landslides
depends on landslide properties including velocity, size, and frequency
of occurrence. However, constraints on size, in particular, subsurface
geometry, are lacking because these types of landslides rarely fully
evacuate material to create measurable hillslope scars. Here we use
pixel offset tracking with data from the NASA/JPL Uninhabited Aerial
Vehicle Synthetic Aperture Radar (UAVSAR) to measure the
three-dimensional surface deformation of 134 slow-moving landslides in
the northern California Coast Ranges. We apply volume conservation to
infer the actively deforming thickness, volume, geometric scaling, and
frictional strength of each landslide. These landslides move at average
rates between ~0.1–3 m/yr and have areas of
~6.1 x 10^3–2.35 x 10^6 m^2, inferred mean
thicknesses of ~1.1–25 m, and volumes of
~7.01 x 103–9.75 x 10^6 m^3. The best-fit
volume-area geometric scaling exponent is γ ~ 1.2–1.5,
indicating that these landslides fall between typical soil and bedrock
landslide scaling. A rollover in the scaling relationship suggests that
the largest landslide complexes in our dataset become large primarily by
increasing in area rather than thickness. In addition, the slow-moving
landslides display scale-dependent frictional strength, such that large
landslide tend to be weaker than small landslides. This decrease in
frictional strength with landslide size is likely because larger
landslides are composed of higher proportions of weak material. Our work
shows how state-of-the-art remote sensing techniques can be used to
better understand landslide processes and quantify their contribution to
landscape evolution and hazards to human safety.