Abstract

Accurately assessing landform evolution and quantifying rapid environmental changes are gaining importance in the context of monitoring techniques in alpine environments. In the European Alps, glaciers and rock glaciers are among the most characteristic cryospheric components bearing the most prolonged monitoring periods. This study introduces a rigorous procedure to quantify rock glacier kinematics and their associated uncertainty derived from sequential unmanned aerial vehicle (UAV) surveys. High-resolution digital elevation models (DEMs) and orthomosaics are derived from UAV image series combined with structure from motion (SfM) photogrammetry techniques. Multitemporal datasets are employed for measuring spatially continuous rock glacier kinematics using image matching algorithms. This procedure is tested on seven consecutive (from 2016 to 2019) UAV surveys of Tsarmine rock glacier, Valais Alps, Switzerland. The evaluation of superficial displacements was performed with simultaneous in-situ differential global navigation satellite system (GNSS) measurements. During the study period, the rock glacier doubled its overall frontal velocity, from around 5 m yr−1 between October 2016 and June 2017 to more than 10 m yr−1 between June and September 2019. Using the adequate UAV survey acquisition, processing, and validation steps, we almost achieved the same accuracy as the GNSS-derived velocities. Nevertheless, the proposed monitoring method provides accurate surface velocity fields values, which allow an enhanced description of the current rock glacier dynamics and its surface expression.

Highlights

  • Rock glaciers represent one of the most iconic and abundant landforms inside the mountain permafrost realm (Barsch, 1996; Jones et al, 2018)

  • We propose that repeated unmanned aerial vehicle (UAV) surveys provide complementary information to improve our understanding of rock glacier kinematics and dynamics, and a potential technique to be integrated into the mountain permafrost monitoring programs

  • Velocities obtained by in-situ global navigation satellite system (GNSS) surveys and UAV-derived data were analysed in detail for five consecutive periods from

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Summary

Introduction

Rock glaciers represent one of the most iconic and abundant landforms inside the mountain permafrost realm (Barsch, 1996; Jones et al, 2018). They have been regarded as useful indicators of past and present permafrost conditions in different mountain chains (Kellerer-Pirklbauer et al, 2008; Konrad et al, 1999; Sorg et al, 2015; Winkler and Lambiel, 2018). The dynamics of rock glaciers includes the acting forces on the creeping body and the 3D changes over time (Kääb, 2005). Whereas the former cannot be directly measured by remote sensing techniques but from modelling approaches (e.g. Müller et al, 2016), the latter.

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