Unmanned aerial vehicle‐based mapping of turf‐banked solifluction lobe movement and its relation to material, geomorphometric, thermal and vegetation properties

Abstract

Solifluction is one of the most widespread periglacial processes with low annual movement rates in the range of —millimeters to centimeters. Traditional methods to assess solifluction movement usually have low spatial resolution, which hampers our understanding of spatial movement patterns and the factors controlling them. In this study, we (a) test the applicability of unmanned aerial vehicle (UAV)‐based structure‐from‐motion photogrammetry in comparison to a traditional total station survey to map surface movement of a turf‐banked solifluction lobe (TBL) in the Turtmann Valley (Switzerland). We then (b) relate the detected movement patterns to potential geomorphometric, material, thermal and vegetation controls, which we assessed using geomorphic and vegetation mapping, electrical resistivity surveys and temperature loggers. Our results show that (a) UAV‐based mapping can detect solifluction movement with high spatial resolution (one point per m2, total > 900 points) and rates and patterns consistent with a total station survey, but requires careful measurement set‐up and analysis; and (b) movement rates differ between lobe tread, riser and a ridge feature. Differences can be explained by heterogeneous material, geomorphometric, thermal and vegetation properties of the TBL, which promote different solifluction processes. Our study demonstrates the applicability of UAV‐based mapping in solifluction research and improves our understanding of solifluction processes and landform development.

Kinematics and geomorphological changes of a destabilising rock glacier captured from close-range sensing techniques (Tsarmine rock glacier, Western Swiss Alps)

“…Alongside, new developments in the domain of image processing and photogrammetric techniques, such as structure from motion (SfM), have burgeoned during the last years (James and Robson, 2012;Westoby et al, 2012;Smith et al, 2016;Anderson et al, 2019). As such, the so-called UAV-SfM photogrammetric workflows have been used in different domains, such as the monitoring of landslide kinematics (Lucieer et al, 2013;Clapuyt et al, 2017) and for studying glacial (Ryan et al, 2015;Fugazza et al, 2018;Rossini et al, 2018;Benoit et al, 2019) and periglacial processes (Eichel et al, 2020;Hendrickx et al, 2020), among other applications. Until now, only a few study cases have reported on rock glacier monitoring by relying exclusively on UAV-SfM techniques (Dall'Asta et al, 2017;Vivero and Lambiel, 2019;Halla et al, 2021;Bearzot et al, 2022) or by a combination of UAV-SfM with additional remote sensing data (Kaufmann et al, 2018;Groh and Blöthe, 2019;Fey and Krainer, 2020;Blöthe et al, 2021).…”

Characteristic periglacial topography: Multi‐scale hypsometric analysis of cryoplanated uplands in eastern Beringia

“…Most geomorphometric studies have focused on fluvial, glacial, and arid geomorphic landscapes (e.g., [68][69][70] ). Applications of geomorphometry in the periglacial realm, although of long standing (e.g., 45,[71][72][73][74][75][76][77][78][79] ), are scattered widely and do not form a cohesive body of literature, particularly with respect to erosional landforms. As in other areas of geomorphometry, a locus has developed in periglacial geomorphometric research involving the use of DEMs, often in concert with remotely sensed products.…”

Evaluation of the Influence of Processing Parameters in Structure-from-Motion Software on the Quality of Digital Elevation Models and Orthomosaics in the Context of Studies on Earth Surface Dynamics

“…Other potential applications may include, for instance, studies of alluvial fans [68], glacial landforms [40,69], glacier lake outburst floods [70,71] or aeolian landforms [72][73][74]. Furthermore, the scripts can be used for modelling various small objects, e.g., in archaeology [75] or geomorphology [76]. The presented scripts enabled a quick launch and systematic work, thereby making it possible to process more efficiently, e.g., several dozen large sets of images in agriculture [77], where each field can be used as a separate point of interest.…”