Inferring the Subsurface Geometry and Strength of Slow-Moving Landslides Using 3-D Velocity Measurements From the NASA/JPL UAVSAR

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 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 ∼0.1–2 m/yr and have active areas of ∼6.10 × 10^3–2.35 × 10^6 m^2, inferred mean thicknesses of ∼1.1 – 25 m, and volumes of ∼7.01 × 10^3 – 9.75 × 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 data set 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.