An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

Abstract

Rock glaciers are widespread periglacial landforms in mountain regions like the European Alps. Depending on their ice content, they are characterized by slow downslope displacement due to permafrost creep. These landforms are usually mapped within inventories, but understand their activity is a very difficult task, which is frequently accomplished using geomorphological field evidences, direct measurements, or remote sensing approaches. In this work, a powerful method to analyze the rock glaciers’ activity was developed exploiting the synthetic aperture radar (SAR) satellite data. In detail, the interferometric coherence estimated from Sentinel-1 data was used as key indicator of displacement, developing an unsupervised classification method to distinguish moving (i.e., characterized by detectable displacement) from no-moving (i.e., without detectable displacement) rock glaciers. The original application of interferometric coherence, estimated here using the rock glacier outlines as boundaries instead of regular kernel windows, allows describing the activity of rock glaciers at a regional-scale. The method was developed and tested over a large mountainous area located in the Eastern European Alps (South Tyrol and western part of Trentino, Italy) and takes into account all the factors that may limit the effectiveness of the coherence in describing the rock glaciers’ activity. The activity status of more than 1600 rock glaciers was classified by our method, identifying more than 290 rock glaciers as moving. The method was validated using an independent set of rock glaciers whose activity is well-known, obtaining an accuracy of 88%. Our method is replicable over any large mountainous area where rock glaciers are already mapped and makes it possible to compensate for the drawbacks of time-consuming and subjective analysis based on geomorphological evidences or other SAR approaches.

Rock glacier inventory of the western Nyainqêntanglha Range, Tibetan Plateau, supported by InSAR time series and automated classification

“…This can be difficult to achieve in high mountain areas, where heavy snow fall may lead to decorrelation of InSAR in winter 16 . Using exclusively snow‐free summer acquisitions or exploiting the low coherence associated with moving landforms could be an alternative in those regions 88 . Our automated classification approach is likely to work well in other regions with dry winter climates, such as the central and northern TP.…”

Rock glaciers automatic mapping using optical imagery and convolutional neural networks

“…Although being relatively precise, this methodology requires a pre‐existing inventory in the region for calibration. Another popular methodology is based on (interferometric synthetic aperture radar (InSAR) detection, which allows the detection of moving areas of actively creeping rock glaciers 11,12 . Although this method is already operational for mapping and monitoring active rock glaciers, it does not allow inactive landforms to be spotted.…”

Incorporating kinematic attributes into rock glacier inventories exploiting InSAR data: preliminary results in eleven regions worldwide

“…The second limit related to InSAR concerns moving areas with slow movements (i.e., with velocities slower than 3 cm/yr), mainly investigated using annual interferograms with Sentinel-1 and ALOS-2 (Barboux et al, 2014;Yague-Martinez et al, 2016). With long time intervals (i.e., annual), the quality of the interferograms is lower due to loss of phase coherence (Barboux et al, 2014;Bertone et al, 2019;Klees and Massonnet, 1998;Touzi et al, 1999). Slow movements are therefore more complicated to be assessed with enough precision, and the reliability is consequently lower.…”

“…First, the aim of this approach is to implement the kinematic information of rock glaciers affected by movement, without paying too much attention to the slowest landforms. Second, rock glaciers without movements or with slow movements are more difficult to investigate, because the quality of the InSAR signal of yearly interferograms is generally lower, as explained above (Barboux et al, 2014;Bertone et al, 2019;Touzi et al, 1999); consequently, relict and slow-moving rock glaciers are more easily omitted or classified as undefined. For the above reasons, some compiled inventories only provide preliminary results, which still need improvement and investigation.…”