Multi‐temporal 3D point cloud‐based quantification and analysis of geomorphological activity at an alpine rock glacier using airborne and terrestrial LiDAR

Abstract

Change analysis of rock glaciers is crucial to analyzing the adaptation of surface and subsurface processes to changing environmental conditions at different timescales because rock glaciers are considered as potentially unstable slopes and solid water reservoirs. To quantify surface change in complex surface topographies with varying surface orientation and roughness, a full three‐dimensional (3D) change analysis is required. This study therefore proposes a novel approach for accurate 3D point cloud‐based quantification and analysis of geomorphological activity on rock glaciers. It is applied to the lower tongue area of the Äußeres Hochebenkar rock glacier, Ötztal Alps, Austria. Multi‐temporal and multi‐source topographic LiDAR data are used to quantify surface changes and to reveal their spatial and temporal characteristics at different timescales within the period 2006–2018. LiDAR‐based examinations are complemented with subsurface characteristics obtained from electrical resistivity tomography. This combined approach reveals active and variable spatial and temporal surface dynamics in the investigated area, with minimum detectable change between 0.09 and 0.65 m at 95% confidence. Given that this approach overcomes current uncertainties in established methods of differentiating complex rock glacier surfaces, we consider it a valuable addition that can be applied to objects of similar properties such as landslides or glaciers.

A New Method for Positional Accuracy Control for Non-Normal Errors Applied to Airborne Laser Scanner Data

“…The RMSE and the mean error ranged from 0.19 to 0.23 m, and from 0.13 to 0.16 m, respectively, being the slope and the undergrowth vegetation the most important factors influencing DTM accuracy. In [6], as part of a multitemporal study of an alpine rock glacier, the signed discrepancy for stable areas yielded a standard deviation of 0.23 m for a time span of 5 years. LiDAR precision is also evaluated for physical features, as for example in [7], where the LiDAR error for dimensional features of a bridge and several fence posts reach up to 23.5%.…”

Disaggregating surface change mechanisms of a rock glacier using terrestrial laser scanning point clouds acquired at different time scales

“…Disaggregating the changes related to this deformation represents a valuable step in interpreting how rock glaciers move, as well as what drives this movement. Approaches to support these interpretations based on in situ monitoring, such as the distribution of electrical resistivity tomography values (Zahs et al, 2019) or ground temperature records from boreholes (Kenner et al, 2017) are also of value. To distinguish changes at the surface, which are assumed to be in the order of a few centimeters within timescales of few weeks, 3D topographic data at high spatial resolution are required.…”

“…These can be obtained using lidar systems (e.g. Bollmann et al, 2012;Micheletti et al, 2016;Zahs et al, 2019), which provide highaccuracy and high-precision 3D measurements of a surface at centimeter-scale point spacing (generally equating to spatial resolution).…”

“…While Zahs et al (2019) have applied this approach to existing datasets of the rock glacier Äußeres Hochebenkar, the processes that cause the observed changes may induce movement along different predominant directions. Examining change in multiple directions may therefore be required in order to distinguish these processes.…”

“…Repeated data acquisitions using lidar have seen increasing use in order to detect and quantify rock glacier surface change (Bollmann et al, 2012;Bollmann et al, 2015;Micheletti et al, 2016;Klug et al, 2017;Zahs et al, 2019). To date, most studies have used monitoring intervals of one year or longer.…”