Abstract

The Slumgullion landslide, located in southwestern Colorado, has been active since the early 1700s and current data suggests that the most active portion of the slide creeps at a rate of ~1.5–2.0 cm/day. Accurate deformation measurement techniques are vital to the understanding of persistent, yet slow-moving landslides like the Slumgullion. The factors that affect slope movements at the Slumgullion are on-time scales that are well suited towards a remotely sensed approach to constrain the 12 different kinematic units that make up the persistent creeping landslide. We derive a time series of motion vectors (magnitude and direction) using subpixel offset techniques from very high resolution TerraSAR-X Staring Spotlight ascending/descending data as well as from a novel high-resolution amalgamation of airborne lidar and unmanned aerial systems (UAS) Structure from Motion (SfM) digital surface model (DSM) hillshades. Deformation rates calculated from the spaceborne and airborne datasets show high agreement (mean difference of ~0.9 mm/day), further highlighting the potential for the monitoring of ongoing mass wasting events utilizing unmanned aircraft systems (UAS) We compare pixel offset results from an 11-day synthetic aperture radar (SAR) pair acquired in July of 2016 with motion vectors from a coincident low-cost L1 only Global Navigation Satellite System (GNSS) field campaign in order to verify the remotely sensed results and to derive the accuracy of the azimuth and range offsets. We find that the average azimuth and range pixel offset accuracies utilizing the methods herein are on the order of 1/18 and 1/20 of their along-track and slant range focused ground pixel spacing values of 16.8 cm and 45.5 cm, respectively. We utilize the SAR offset time series to add a twelfth kinematic unit to the previously established set of eleven unique regions at the site of an established minislide within the main landslide itself. Lastly, we compare the calculated rates and direction from all spaceborne- and airborne-derived motion vectors for each of the established kinematic zones within the active portion of the landslide. These comparisons show an overall increased magnitude and across-track component (i.e., more westerly angles of motion) for the descending SAR data as compared to their ascending counterparts. The processing techniques and subsequent results herein provide for an improved knowledge of the Slumgullion landslide’s kinematics and this increased knowledge has implications for the advancement of measurement techniques and the understanding of globally distributed creeping landslides.

Highlights

  • TThhee SSlluummgguulllliioonn LLaannddsslliiddee, llooccaatteeddnneeaarrLLaakkee CCiittyy iinn tthhee SSaann JJuuaann MMoouunnttaaiinnss ooff ssoouutthhwweesstt CCoolloorraaddoo, iiss aaddeeeepp-s-seeaatetedd,crcereepeipnignglanladnsdlisdliedaenadnhdashbaesebneaecntivacetsivinecesitnhceeetahrelye1a7r0ly0s1[710–03s].[T1–h3e]a. cTtihvee apcotirvtieonpoorfttiohne solfidtehecrseleidpes ocrneteopps oofnatnoipnaocftiavneihniasctotirvice shliosptoerfiacilsulorepethfaatiloucrceutrhreadt oocvceurr7r0e0d yoevaerrs 7a0g0o yaenadrsisaoguotalinndedisinouFtilginuerde 1in

  • The magnitude of the deformation vectors derived in this study is similar to past findings, and the angle of the deformation is in line with the local aspect and topographic bounds of the slide [6,7,12,81,82]

  • We found the matching cell in the synthetic aperture radar (SAR) offset image that corresponds closest to the ground control points (GCPs) location using precise latitude and longitude look-up arrays, and determined the deformation vector at that location along with a separate vector for the average nine-cell window centered on that pixel

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Summary

Introduction

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