Kinematic Parameter Inversion of the Slumgullion Landslide Using the Time Series Offset Tracking Method With UAVSAR Data

Abstract

The Slumgullion landslide in the San Juan Mountains of Colorado is a translational debris slide whose active part has been moving for at least 300 years. To further study the kinematic characteristics of the spatiotemporal domain of landslides, we establish a kinematic model based on the behavior of the Slumgullion landslide. The kinematic parameters are inverted with 45 sets of surface displacement fields measured by the time series offset tracking method using uninhabited aerial vehicle synthetic aperture radar (UAVSAR) data obtained for the period from August 2011 to November 2013. The inversion results indicate that the Slumgullion landslide moves with an average velocity of up to 1.2 cm/day and presents obvious seasonal changes in velocity. According to the change of sliding velocity, the head and tail of the Slumgullion landslide tend to be stable, whereas the neck of the landslide is accelerating. The topography has an important influence on the kinematic parameters. Based on the kinematic parameters, we identify the main geological structures of the Slumgullion landslide, including tension cracks, strike‐slip faults, and thrust faults. The geological structures inferred by the kinematic parameters are consistent with a geological interpretive map. We derive more detailed kinematic characteristics for these structures using the obtained the kinematic parameters and infer two previously unmapped thrust faults. Additionally, we also analyze the relationship between the meteorology and the seasonal velocity of the Slumgullion landslide. The consistency between the periodic changes in meteorology (mainly including precipitation and snowmelt) and the seasonal velocity further verifies the rationality of using the kinematic model.

High-Resolution Spaceborne, Airborne and In Situ Landslide Kinematic Measurements of the Slumgullion Landslide in Southwest Colorado

“…We note the minislide region as the small area of rapid deformation in the lower one-third of the slide shown within the white ovals in Figure 5. This minislide zone has been found in two prior airborne SAR-based studies [6,20]. We created a new kinematic unit (#12) around this area of rapid motion by summing all SAR offset deformation grids and then defining the kinematic zone 12 region We note the minislide region as the small area of rapid deformation in the lower one-third of the slide shown within the white ovals in Figure 5.…”

“…We created a new kinematic unit (#12) around this area of rapid motion by summing all SAR offset deformation grids and then defining the kinematic zone 12 region We note the minislide region as the small area of rapid deformation in the lower one-third of the slide shown within the white ovals in Figure 5. This minislide zone has been found in two prior airborne SAR-based studies [6,20]. We created a new kinematic unit (#12) around this area of rapid motion by summing all SAR offset deformation grids and then defining the kinematic zone 12 region based on the increased accumulated deformation values in the minislide region as compared to the surrounding cells' values.…”

“…Past research has defined 11 distinct kinematic units at the Slumgullion, and these zones deform in diverse patterns and rates [18,19]. However, recent research has highlighted an area of increased deformation in the lower one-third of the landslide, and we add this minislide region as the twelfth kinematic unit [6,20].…”

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

“…The first campaign was implemented by the Brigham Young University using an X-band sensor, with the purpose of correlating the measured movements to the soil water content [24]. More recently, some studies exploiting airborne L-band remote sensing have been presented [25][26][27]. However, so far, the use of satellite technologies in the literature was limited, despite they can provide a cost-effective and continuous update of the landslide state.…”

Polarimetric Stationarity Omnibus Test (PSOT) for Selecting Persistent Scatterer Candidates with Quad-Polarimetric SAR Datasets

“…The PSI can identify the targets, persistent scatterers (PS), with stable scattering characteristics on the ground and monitor the surface deformation based on the reliable phase and amplitude information. PSI is widely used in volcanoes, earthquakes, urban subsidence, and landslides [9][10][11][12][13][14]. Especially in urban areas, artificial buildings in urban areas can be considered as ideal persistent scatterers (PS) [15], and the PSI technology is based on the PSs to explore the impact of human or natural activities on cities [16].…”