Monitoring Rock Glacier Kinematics with Satellite Synthetic Aperture Radar

Active rock glaciers represent the best visual expression of mountain permafrost that can be mapped and monitored directly using remotely sensed data. Active rock glaciers are bodies that consist of a perennially frozen ice/rock mixture and express a distinct flow-like morphology indicating downslope permafrost creep movement. Annual rates of motion have ranged from a few millimeters to several meters per year, varying within the annual cycle, from year to year, as well as at the decennial time scale. During the last decade, in situ observations in the European Alps have shown that active rock glaciers are responding almost synchronously to inter-annual and decennial changes in ground temperature, suggesting that the relative changes of their kinematics are a general indicator of the evolution of mountain permafrost conditions. Here, we used satellite radar interferometry (InSAR) to monitor the rate of motion of various active rock glaciers in the Swiss Alps, Qeqertarsuaq (Western Greenland), and the semiarid Andes of South America. Velocity time series computed with Sentinel-1 SAR images, regularly acquired since 2014, every six days over Europe and Greenland and every 12 days over the Andes, show annual fluctuations, with higher velocities at the end of the summer. A JERS-1 image pair of 1996 and stacks of very high-resolution SAR images from TerraSAR-X and Cosmo-SkyMed from 2008 to 2017 were analyzed using InSAR and offset tracking over the Western Swiss Alps in order to extend the main observation period of our study. A quantitative assessment of the accuracy of InSAR and offset tracking was performed by comparison with in situ methods. Our results for the three different study regions demonstrate that Sentinel-1 InSAR can complement worldwide in situ measurements of active rock glacier kinematics.


Introduction
Permafrost is a specific thermal condition that allows for the formation and preservation of ice in the ground as the associated ground temperature stays permanently at or below 0 • C. In mountain areas, permafrost underlays large areas at all latitudes worldwide [1,2]. Because of the influence of mountain topography on permafrost properties, the frozen ground in mountainous terrain is moving and considerable volumes of debris or fractured rocks are continuously displaced This rock glacier is about 300 m wide and 500 m long and has also been integrated into PERMOS. Displacement measurements started in 2004 using GNSS campaigns carried out seasonally, while two permanent mono-frequency GNSS stations have been in operation since 2012 and 2016, respectively. The deformation field of the rock glacier is complex, with maximum speeds locally exceeding two meters per year, while surface velocities over the main front are only a few centimeters per year.
human-induced impacts, is, generally, only done based on expert knowledge. On the basis of visual interpretations of optical imagery, sometimes combined with in situ observations, this approach induces subjectivity-related biases and a limited reliability of the analysis. Monitoring efforts of rock glacier kinematics in the Central Andes are restricted to a few sites and has taken place since, generally, less than 10 years ago. Differential GNSS campaigns were, for example, have been performed annually since 2009 for the Tapado and Las Liebres rock glaciers in Chile [62]. In the same area, dynamics of rock glaciers have also been reconstructed based on remote sensing [63]. In addition, recently, repeated UAV surveys have been performed for Dos Lenguas (Argentina, Figure  1e, [64]) and El Paso rock glaciers. In this context, satellite InSAR has a high potential for studying rock glacier kinematics over large areas of the semiarid Chilean/Argentinean Andes in order to improve our understanding of regional dynamics of rock glaciers, as well as to investigate local cases [33,65].

Qeqertarsuaq (Greenland)
Qeqertarsuaq (Disko Island) is the largest island in Greenland, located off the Central West Coast at 53 • W, 70 • N and covering 8575 km 2 . It is mainly mountainous, with large glaciers and ice caps covering up to 20% of the total land area [46]. The landscape is characterized by cirque-carved lava plateaus, steep U-shaped valleys, and fjords. The average elevation of Qeqertarsuaq is~500 m a.s.l., with the highest mountains found in the north and northeastern region [47]. The island's highest peak is at 1905 m a.s.l. The mean annual air temperature at the Arctic Station on the southernmost part of Qeqertarsuaq is −3.0 • C ± 1.8 • C, with an overall increase of 0.2 • C per year between 1991 and 2011 [48]. Geologically, Qeqertarsuaq belongs to the Tertiary volcanic province of West Greenland, composed of plateau basalts [49].
Qeqertarsuaq is classified in the zone of continuous permafrost, and rock glaciers are common on the island both inland and especially along its eastern shores [10] which suggests that the high frequency of rock glaciers on Qeqertarsuaq is due to the high weathering rates of the basaltic rocks. Rock glaciers on Qeqertarsuaq strongly vary in length and thickness. Lobate rock glaciers are typically talus-derived and ice-cemented and collectively estimated as 30 to 300 m long and 10 to 30 m thick, with a general surface slope of only 5 to 25 • while the frontal lobe slope inclined up to 35 to 50 • [10,12]. Furrows and ridges form a relief up to 5 m on large rock glaciers and less than 2 m on smaller ones. According to [12], lobate rock glaciers are predominant on north-facing valley wall slopes and are rare on south-facing Remote Sens. 2020, 12, 559 5 of 24 slopes. Tongue-shaped rock glaciers reach greater lengths of 500 to 6000 m with a thickness of 20 to 75 m. Frontal slopes are similarly inclined as lobate rock glaciers. A main difference is the presence of glaciers at the upper end of the majority of tongue-shaped rock glaciers, suggesting a glacial origin and ice-cored interior [12] and making them difficult to be distinguished from debris-covered glaciers. These rock glaciers generally form in steeper terrain and below cirque headwalls. Ridge and furrow topography are equally observed, however, appears to occur mainly towards the downstream end of the rock glacier. Spatulate rock glaciers are less frequent on Qeqertarsuaq. They are largely tongue-shaped rock glaciers, but with a much broader, spatulate-like front, which forms when the rock glacier flows onto a less constrained so-called "trunk" valley and spreads laterally [12,13]. This spread often results in the formation of two distinct lobes or tongues. We focus our analyses on Manissuarsuk, a large (1 × 3 km) and tongue-shaped northeastern oriented rock glacier along the eastern shores of Qeqertarsuaq (Figure 1c).

Tapado/Agua Negra Region (Chilean/Argentinian Andes)
The Tapado/Agua Negra region (2800 km 2 for the footprint of the satellite images used in this work at approximately 70 • W and 30 • S) in the semiarid Chilean/Argentinean Andes corresponds to the upper part of the Elqui (Chile) and Jachal (Argentina) river catchments. It lies mostly above 2000 m a.s.l., with many mountain slopes and valleys above 4000 m a.s.l. From a climatological point of view, this semiarid portion of the Central Andes exhibits annual precipitations below 500 mm at 3200 m a.s.l. [50], with a strong influence of the ENSO (El Niño Southern Oscillation). Air temperature displays a regional 0 • C isotherm around 4200 m a.s.l. [51] and the warming measured is around 0.2 to 0.4 • C/decade at 3000 m a.s.l. [52]. Depending on solar incoming radiation, permafrost is present on most slopes above 4000 m a.s.l. [53]. For the Chilean side, more than half of the region is favorable to permafrost occurrence [51] with local irregularities due to the spatial variability of the ground thermal regime, the lithology, or the glacio-geomorphological characteristics of the terrain.
Because of the dry conditions, glaciers in the Tapado/Agua Negra region are scarce and the perennial cryosphere is dominated by rock glaciers and transitional landforms from debris-covered glaciers to rock glaciers, that is, ice-debris complexes [54,55]. Accordingly, the exceptionally high spatial density of rock glaciers in the central Andes has spurred controversial debates on their hydrological significance [51,53,56]. In Chile and Argentina, the rock glacier thematic is also important and much discussed on all political levels in connection to water resources and mining activities, which has led to substantial efforts from public authorities to evaluate the cryospheric resources in their respective territories [57]. For that purpose, comprehensive inventories of glaciers, rock glaciers, ice-debris complexes, and permanent snow patches have recently been released at the country scale in Argentina [58] and Chile [59]. Those inventories rely on geomorphological features indicative of the presence of ice-rich permafrost, mainly rock glaciers, mapped from morphological evidences as retrieved from aerial and satellite imagery.
Similar to what is observed in the Alps [3,41], some cases of rock glacier destabilization observed in this region suggest that the geomorphological processes related to rock glacier dynamics is changing because of warming conditions in the ground [60,61]. The assessment of the activity status of the rock glacier, which is of crucial importance for further studying their sensitivity to climate-and human-induced impacts, is, generally, only done based on expert knowledge. On the basis of visual interpretations of optical imagery, sometimes combined with in situ observations, this approach induces subjectivity-related biases and a limited reliability of the analysis. Monitoring efforts of rock glacier kinematics in the Central Andes are restricted to a few sites and has taken place since, generally, less than 10 years ago. Differential GNSS campaigns were, for example, have been performed annually since 2009 for the Tapado and Las Liebres rock glaciers in Chile [62]. In the same area, dynamics of rock glaciers have also been reconstructed based on remote sensing [63]. In addition, recently, repeated UAV surveys have been performed for Dos Lenguas (Argentina, Figure 1e, [64]) and El Paso rock glaciers. In this context, satellite InSAR has a high potential for studying rock glacier kinematics over large areas of the semiarid Chilean/Argentinean Andes in order to improve our understanding of regional dynamics of rock glaciers, as well as to investigate local cases [33,65].

SAR Interferometry
InSAR is a popular and widely used application in mountain areas [37,[66][67][68], as it allows systematic and continuous monitoring of the movement in the satellite line-of-sight (LOS) of entire landforms at a scale ranging from individual slope faces to whole mountain ranges. The InSAR analyses over representative rock glaciers in the Western Swiss Alps, Qeqertarsuaq, and the semiarid Andes in Chile and Argentina were mainly performed with C-band (wavelength 5.6 cm) Sentinel-1 data of the time period 2015 to 2019 [69]. Additionally, a L-band (wavelength 3.1 cm) JERS-1 SAR image pair of 1996 [70] and stacks of very high-resolution summer X-band (wavelength 23.5 cm) SAR images from TerraSAR-X from 2008 to 2012 over the Western Swiss Alps [71] were considered in order to extend the observation period of our study. Sensors, acquisition modes, acquisition periods, time intervals, and pixel resolution of the satellite SAR image pairs used in our study over the different study regions are summarized in Table 1. Processing of SAR satellite data, for the projects discussed here, involves several steps and is carried out with the GAMMA software [72]. In general, these include initial preprocessing of a reference image acquired in summer to ensure maximum coherence and georeferencing with the respective Digital Elevation Model (DEM). For Switzerland, a very high-resolution DEM (SwissALTI3D © Swisstopo) with a spatial resolution of 2 m and an accuracy of all three dimensions reaching 1 to 3 m in alpine terrain is used, while TanDEM-X at 12 m [73] is chosen for Qeqertarsuaq and the Tapado/Agua Negra region. Subsequently, slave images are coregistered to the reference image with a geometrical approach which includes the scene topography, followed for Sentinel-1 by a refinement of the transformation determined by a spectral diversity method [74]. Should strong phase jumps or insufficient coherence prevail with Sentinel-1 data, images are re-coregistered to acquisitions directly before or after the image of interest. Differential interferograms (DInSAR), including removal of the topographic phase using the DEM, are, then, created in series for variable time periods of 6 to 24 days for Sentinel-1, 88 days for JERS-1, and 11 to 22 days for TerraSAR-X. Multi-looked interferogram generation was done to 4 range and 1 azimuth look for Sentinel-1 [74], 2 range and 6 azimuth look for JERS-1 [75] and 3 range and 3 azimuth look for TerraSAX-1 [37]. Phase unwrapping to render absolute LOS movement values is achieved using a minimum cost flow (MCF) algorithm [72] and choosing a reference point close to the active rock glacier of interest. Adaptive filtering of the interferograms to reduce phase noise was not performed before movement computation to not smooth the displacement pattern and remove the signal of the largest moving parts of the rock glaciers. Atmospheric phase trend corrections with respect to height were, first, applied over the entire area covered by the image and, then, refined to particular smaller areas around the rock glaciers. Velocity and coherence data were, Remote Sens. 2020, 12, 559 7 of 24 then, extracted for the rock glaciers of interest contained in a specified frame, which was displayed in external programs for coherence levels >0.5. Conversion from LOS to displacement along the maximum slope direction was accomplished by use the DEM filtered over a distance of 200 m in order to smooth out local steps. A vector representing the assumed direction of motion based on the slope and aspect of the filtered DEM and LOS vectors for each sensor were calculated and the per pixel LOS correction factor was calculated by scalar product of the two vectors.

SAR Offset Tracking
The calculation of displacement fields with SAR data is also possible using offset tracking methods, largely adopted over glaciers in order to overcome InSAR signal decorrelation when using long time intervals or analyzing rapidly moving objects (e.g., [35,[76][77][78]). We used stacks of TerraSAR-X [71] and Cosmo-SkyMed [79] images regularly acquired every summer between 2008 and 2017 over the Western Swiss Alps (Table 1) to retrieve time series of surface velocity maps over the Distelhorn and Tsarmine rock glaciers, respectively, using the offset tracking method of the GAMMA software [35,78]. Using a normalized cross-correlation of chips in amplitude SAR images, offsets are measured using rectangular windows at a set of positions uniformly distributed over the image scene. The size of the correlation matching window sizes was adjusted according to the image resolution to 64 × 64 pixels in range and azimuth for both TerraSAR-X and Cosmo-SkyMed images. In order to obtain an accurate subpixel precision estimate of the correlation peak, the correlation function values were fitted using a biquadratic polynomial surface. The time interval of the image pairs was adjusted according to the expected maximum displacement over the rock glacier to two years for the TerraSAR-X data over the Distelhorn rock glacier and to one year for the Cosmo-SkyMed data over the Tsarmine rock glacier. In both cases, late summer image pairs with short perpendicular baselines were considered. Mismatches or blunders were filtered by applying a threshold to the correlation coefficient (0.1 for both TerraSAR-X and Cosmo-SkyMed data), by iteratively discarding spurious matches based on the angle and size of displacement vectors in the surrounding area, and by using a low-pass filter on the resulting fields [77]. For validation with aerial photo matching and GNSS stations, slant range and azimuth offset fields were first combined to retrieve horizontal surface velocity maps. For comparison to the InSAR displacements computed along the maximum slope direction, slant range and azimuth offset fields were then also computed along the terrain surface determined from the DEM [35]. The final maps were geocoded using the DEM to a 25 m resolution raster.

Distelhorn Rock Glacier (Western Swiss Alps)
The Distelhorn rock glacier (Figures 1a and 2a) is northwest oriented, making it particularly well suited for InSAR investigations using images acquired along descending orbits. Sentinel-1, JERS-1, and TerraSAR-X differential interferograms over 12/6, 88, and 11 days, presented in Figure 2b,c,e,f, respectively, all indicate a clear displacement pattern over large parts of the rock glacier. However, more decorrelation is observed over both the front and at the rooting zone, in particular for the X-band data over 11 days and the C-band data over 12 days. The most complete pattern can be seen in the six days Sentinel-1 interferogram, which allowed us to successfully unwrap the phase to derive the LOS displacement map of Figure 2d. The front of the rock glacier was moving in the summer of 2018 with LOS displacement rates of about 1 to 2 m/a. This is well in agreement, although at a lower spatial resolution, with the results obtained using offset tracking of TerraSAR-X data with a time interval of about two years ( Figure 2g). rock glaciers in Switzerland (e.g, [14,18]). In Figure 3b we notice that Sentinel-1 interferograms, over a 6 day time interval, permit to occasionally derive valid information also during the wintertime, possibly for periods with (cold?) stable snow conditions, in particular without snow melt or snowfall. .

Tsarmine Rock Glacier (Western Swiss Alps)
The Tsarmine rock glacier (Figures 1b and 4a) is smaller and faster than the Distelhorn rock glacier and the SAR interferograms are, thus, more decorrelated. Very high-resolution X-band data over nine days in mid-summer 2017 ( Figure 4c) have a clear fringe pattern only in the central/upper part of the rock glacier, while at the front the fringe pattern is rather confuse. High-resolution C-band data over six days in September 2017 show again reasonable coherence in the central part of the rock glacier, while over the rest of the rock glacier coherence is low. Offset tracking of Cosmo-SkyMed data over one year permits to compute maps of the rock glacier velocity with a fairly good spatial coverage, in particular in the early years of investigations (e.g., between 2010 and 2011, see Figure rock glaciers in Switzerland (e.g, [14,18]). In Figure 3b we notice that Sentinel-1 interferograms, over a 6 day time interval, permit to occasionally derive valid information also during the wintertime, possibly for periods with (cold?) stable snow conditions, in particular without snow melt or snowfall. .

Tsarmine Rock Glacier (Western Swiss Alps)
The Tsarmine rock glacier (Figures 1b and 4a) is smaller and faster than the Distelhorn rock glacier and the SAR interferograms are, thus, more decorrelated. Very high-resolution X-band data over nine days in mid-summer 2017 ( Figure 4c) have a clear fringe pattern only in the central/upper part of the rock glacier, while at the front the fringe pattern is rather confuse. High-resolution C-band data over six days in September 2017 show again reasonable coherence in the central part of the rock glacier, while over the rest of the rock glacier coherence is low. Offset tracking of Cosmo-SkyMed data over one year permits to compute maps of the rock glacier velocity with a fairly good spatial coverage, in particular in the early years of investigations (e.g., between 2010 and 2011, see Figure In Figure 3a we plotted the velocities along the maximum slope direction from JERS-1, TerraSAR-X, and Sentinel-1 InSAR and the velocity along the terrain surface from TerraSAR-X offset tracking over the eastern frontal lobe of the Distelhorn rock glacier, which is moving slower than the western frontal lobe and thus is better suited for InSAR analyses to avoid phase unwrapping mistakes. From 1996 to 2016, only velocities over summer periods (InSAR) or for about two years (offset tracking) are available. They indicate rates of motion between 0.5 and 1 m/a without strong variability over time. Since 2016, much more measurements are available from Sentinel-1, revealing a larger variability and increased velocities up to more than 2 m/a. The enlargement of the Sentinel-1 InSAR results of Figure 3b indicates seasonal variations of the rock glacier velocity, with values higher in autumn and lower in spring, in agreement with the annual cycle observed in situ over other rock glaciers in Switzerland (e.g, [14,18]). In Figure 3b we notice that Sentinel-1 interferograms, over a 6 day time interval, permit to occasionally derive valid information also during the wintertime, possibly for periods with (cold?) stable snow conditions, in particular without snow melt or snowfall.

Tsarmine Rock Glacier (Western Swiss Alps)
The Tsarmine rock glacier (Figures 1b and 4a) is smaller and faster than the Distelhorn rock glacier and the SAR interferograms are, thus, more decorrelated. Very high-resolution X-band data over nine days in mid-summer 2017 ( Figure 4c) have a clear fringe pattern only in the central/upper part of the rock glacier, while at the front the fringe pattern is rather confuse. High-resolution C-band data over six days in September 2017 show again reasonable coherence in the central part of the rock glacier, while over the rest of the rock glacier coherence is low. Offset tracking of Cosmo-SkyMed data over one year permits to compute maps of the rock glacier velocity with a fairly good spatial coverage, in particular in the early years of investigations (e.g., between 2010 and 2011, see

Becs-de-Besson Rock Glacier (Western Swiss Alps)
The complex deformation field of the Becs-de-Besson rock glacier (Figures 1c and 6a) is well visible in the 11 days TerraSAR-X and six days Sentinel-1 differential interferograms of Figure 6b,c,

Becs-de-Besson Rock Glacier (Western Swiss Alps)
The complex deformation field of the Becs-de-Besson rock glacier (Figures 1c and 6a) is well visible in the 11 days TerraSAR-X and six days Sentinel-1 differential interferograms of Figure 6b

Qeqertarsuaq (Greenland)
We focus our analyses on Qeqertarsuaq on Manissuarsuk, a large (1 × 3 km) and tongue-shaped northeastern oriented rock glacier (Figures 1c and 8a). A Sentinel-1 differential interferogram over six days in mid-winter (Figure 8b) very nicely depicts the displacement field of the rock glacier, with good coherence everywhere and larger displacement at the eastern front. The time series of motion at the eastern front of Manissuarsuk ( Figure 9) indicates again that rock glacier activity is generally higher in autumn and lower in spring, although with a larger noise as compared with the Distelhorn (Figure 3b) and Becs-de-Besson rock glaciers (Figure 7) in the Swiss Alps. In this case, maximum velocities are approaching 4 m/a and minimum velocities around 2 m/a.

Qeqertarsuaq (Greenland)
We focus our analyses on Qeqertarsuaq on Manissuarsuk, a large (1 × 3 km) and tongue-shaped northeastern oriented rock glacier (Figures 1c and 8a). A Sentinel-1 differential interferogram over six days in mid-winter (Figure 8b) very nicely depicts the displacement field of the rock glacier, with good coherence everywhere and larger displacement at the eastern front. The time series of motion at the eastern front of Manissuarsuk ( Figure 9) indicates again that rock glacier activity is generally higher in autumn and lower in spring, although with a larger noise as compared with the Distelhorn (Figure 3b

Dos Lenguas Rock Glacier (Agua Negra Region, Argentinian Andes)
Several areas of distinct velocity patterns related to the motion of rock glaciers are observed with InSAR over the Tapado/Agua Negra region. A Sentinel-1 differential interferogram over six days is presented in Figure 10 for one prominent rock glacier of the Agua Negra Region, Dos Lenguas. In this particular case, we observe higher rates of motion at the rooting zone in the east rather than at front(s) in the west. Rates of motion over the center of the rooting zone ( Figure 11) range from 1.5 to 2 m/a, with less amplitude variations of the annual cycle than observed for the Swiss Alps. These rates of motion are very consistent with values obtained from recent studies on the Dos Lenguas rock glacier using a Phantom 3 Advanced Multicopter and Structure from Motion (SfM) techniques [64]. In this study, values ranging from 1.

Dos Lenguas Rock Glacier (Agua Negra Region, Argentinian Andes)
Several areas of distinct velocity patterns related to the motion of rock glaciers are observed with InSAR over the Tapado/Agua Negra region. A Sentinel-1 differential interferogram over six days is presented in Figure 10 for one prominent rock glacier of the Agua Negra Region, Dos Lenguas. In this particular case, we observe higher rates of motion at the rooting zone in the east rather than at front(s) in the west. Rates of motion over the center of the rooting zone ( Figure 11) range from 1.5 to 2 m/a, with less amplitude variations of the annual cycle than observed for the Swiss Alps. These rates of motion are very consistent with values obtained from recent studies on the Dos Lenguas rock glacier using a Phantom 3 Advanced Multicopter and Structure from Motion (SfM) techniques [64]. In this study, values ranging from 1.

Dos Lenguas Rock Glacier (Agua Negra Region, Argentinian Andes)
Several areas of distinct velocity patterns related to the motion of rock glaciers are observed with InSAR over the Tapado/Agua Negra region. A Sentinel-1 differential interferogram over six days is presented in Figure 10 for one prominent rock glacier of the Agua Negra Region, Dos Lenguas. In this particular case, we observe higher rates of motion at the rooting zone in the east rather than at front(s) in the west. Rates of motion over the center of the rooting zone ( Figure 11) range from 1.5 to 2 m/a, with less amplitude variations of the annual cycle than observed for the Swiss Alps. These rates of motion are very consistent with values obtained from recent studies on the Dos Lenguas rock glacier using a Phantom 3 Advanced Multicopter and Structure from Motion (SfM) techniques [64]. In this study, values ranging from 1.

SAR Interferometry
For single measurements at C-band, an error of 6 to 7 mm, partly attributed to noise (1 to 2 mm)

SAR Interferometry
For single measurements at C-band, an error of 6 to 7 mm, partly attributed to noise (1 to 2 mm) and partly to atmospheric artifacts (5 to 6 mm), was estimated in a major validation project over urban areas [80], where a similar high degree of coherence over a multiannual period is typically observed as in 6 to 12 days over rock glaciers. This error translates to a LOS measurement uncertainty of ±0.4 m/a for Sentinel-1 interferograms over six days and of ±0.2 m/a for Sentinel-1 interferograms over 12 days. A similar phase error of one quarter of a phase cycle due to signal noise and atmospheric artefacts is typically observed also at X-band [68]. For TerraSAR-X interferograms over 11 days, this error corresponds to a measurement uncertainty in LOS displacement of ±0.1 m/a. At L-band the total phase error is minor [81], for example, one eighth of a phase cycle, leading to an error in LOS displacement of the JERS-1 interferogram over 88 days of ±0.1 m/a.
One of the permanent mono-frequency GNSS stations over Becs-de-Bosson rock glacier, BdB2, which was installed in 2016 at a location where velocities are rather spatially homogeneous ( Figure 6), was used for a direct validation of the Sentinel-1 InSAR measurements. In local differential mode, with differential postprocessing computed with respect to a permanent local basis, the estimated accuracy of the mean planimetric and altimetric GNSS positioning over 24 h is in the order of +/−2 mm and that of the velocity over a 6 day period in the order of +/−0.24 m/a [43]. The 3D GNSS velocities computed with the average daily positions corresponding to the acquisition dates of the Sentinel-1 images are plotted together with the velocities along the maximum slope direction from Sentinel-1 InSAR in Figure 12a. For the 41 coincident measurement points (Figure 12b), the standard deviation of the velocity difference is 0.21 m/a, while average, minimum, and maximum of the velocity difference are −0.08 m/a, −0.67 m/a, and 0.33 m/a, respectively. Sentinel-1 InSAR is slightly underestimating the GNSS velocities, possibly because the rock glacier is not exactly moving along the steepest slope or as a result of the InSAR spatial resolution on the order of 15 m. On the one hand, over the Tsarmine rock glacier the permanent mono-frequency GNSS station operates in a local differential mode. It is, however, located in a section where the Sentinel-1 interferograms are decorrelated, because the late summer rates of motion are overpassing, since 2015, 6 m/a, i.e., amount to nearly 9 cm in six days (Figure 4). Displacement measurements using GNSS campaigns carried out seasonally, on the other hand, are performed on about 60 positions, including the locations of the permanent GNSS station and the spot of the Sentinel-1 InSAR time-series of Figure  5b. Considering that during the last three years (2016 to 2018) the ratio between the annual rates of motion of these two positions remained constant (factor 0.54), we plotted in Figure 13a the scaled 3D GNSS velocities computed with the average daily positions corresponding to the acquisition dates of the Sentinel-1 images together with the velocities along the maximum slope direction from Sentinel-1 InSAR. Taking into account the scaling of the continuous GNSS data, the correspondence to the On the one hand, over the Tsarmine rock glacier the permanent mono-frequency GNSS station operates in a local differential mode. It is, however, located in a section where the Sentinel-1 interferograms are decorrelated, because the late summer rates of motion are overpassing, since 2015, 6 m/a, i.e., amount to nearly 9 cm in six days (Figure 4). Displacement measurements using GNSS campaigns carried out seasonally, on the other hand, are performed on about 60 positions, including the locations of the permanent GNSS station and the spot of the Sentinel-1 InSAR time-series of Figure 5b. Considering that during the last three years (2016 to 2018) the ratio between the annual rates of motion of these two positions remained constant (factor 0.54), we plotted in Figure 13a the scaled 3D GNSS velocities computed with the average daily positions corresponding to the acquisition dates of the Sentinel-1 images together with the velocities along the maximum slope direction from Sentinel-1 InSAR. Taking into account the scaling of the continuous GNSS data, the correspondence to the Sentinel-1 InSAR results is impressive. The scatter plot of scaled GNSS and Sentinel-1 velocities (Figure 13b) indicates even more clearly the very good accordance. For the 45 coincident measurement points, the standard deviation of the velocity difference is 0.22 m/a, whereas average, minimum, and maximum velocity differences are 0.03 m/a, −0.40 m/a, and 0.50 m/a, respectively. The results of the displacement measurements from the GNSS campaigns carried out seasonally are also shown in Figure 13a. In real-time GNSS kinematic mode, with the receiver left calculating its position for a few seconds, the standard deviation of positioning during this time lapse is usually less than 1 cm in the horizontal component and less than 2 cm in the vertical one [82]. As expected, differential GNSS measurements miss the strong seasonal variations, but the order of magnitude of the rate of motion fits the Sentinel-1 InSAR results.
On the one hand, over the Tsarmine rock glacier the permanent mono-frequency GNSS station operates in a local differential mode. It is, however, located in a section where the Sentinel-1 interferograms are decorrelated, because the late summer rates of motion are overpassing, since 2015, 6 m/a, i.e., amount to nearly 9 cm in six days (Figure 4). Displacement measurements using GNSS campaigns carried out seasonally, on the other hand, are performed on about 60 positions, including the locations of the permanent GNSS station and the spot of the Sentinel-1 InSAR time-series of Figure  5b. Considering that during the last three years (2016 to 2018) the ratio between the annual rates of motion of these two positions remained constant (factor 0.54), we plotted in Figure 13a the scaled 3D GNSS velocities computed with the average daily positions corresponding to the acquisition dates of the Sentinel-1 images together with the velocities along the maximum slope direction from Sentinel-1 InSAR. Taking into account the scaling of the continuous GNSS data, the correspondence to the Sentinel-1 InSAR results is impressive. The scatter plot of scaled GNSS and Sentinel-1 velocities (Figure 13b) indicates even more clearly the very good accordance. For the 45 coincident measurement points, the standard deviation of the velocity difference is 0.22 m/a, whereas average, minimum, and maximum velocity differences are 0.03 m/a, −0.40 m/a, and 0.50 m/a, respectively. The results of the displacement measurements from the GNSS campaigns carried out seasonally are also shown in Figure 13a. In real-time GNSS kinematic mode, with the receiver left calculating its position for a few seconds, the standard deviation of positioning during this time lapse is usually less than 1 cm in the horizontal component and less than 2 cm in the vertical one [82]. As expected, differential GNSS measurements miss the strong seasonal variations, but the order of magnitude of the rate of motion fits the Sentinel-1 InSAR results.  Standard normalized image cross-correlation techniques enable surface displacement measurements from repeat optical images at subpixel horizontal accuracy [83,84]. We matched repeat orthorectified aerial images provided by Swisstopo, the Swiss national mapping agency, with a spatial resolution of 0.4 m acquired on 03.09.2014 and 21.09.2017 over the Distelhorn rock glacier. From matches over stable ground outside the rock glacier we estimate a displacement accuracy of ±0.15 m, that is, ±0.05 m/a. The horizontal displacement field from offset tracking in repeat orthoimages is compared to the Sentinel-1 InSAR LOS displacement field from 02.08.2018 to 08.08.2018 in Figure 14 along with the difference map between the two measurements. The results of Figure 14 indicate a good spatial correspondence between aerial photo matching and Sentinel-1 InSAR, but on the southern tip of the rock glacier the interferogram was not correctly unwrapped. Further discrepancies can be observed on the edges of the fastest moving parts of the rock glacier front. The scatter plot of the aerial photo matching and Sentinel-1 LOS velocities (Figure 15a) indicates the effect of the different time intervals (three years as compared with six days) and of the satellite look direction. In Figure 15b, we empirically fitted the Sentinel-1 LOS velocities to the aerial photo matching velocities by scaling them with a factor of −1.23 in order to maximize the one-to-one match and account, therefore, for these two effects. After scaling, the standard deviation of the velocity difference for the 2237 coincident measurement points is 0.30 m/a, while average, minimum and maximum velocity differences are 0.01 m/a, −2.09 m/a, and 2.84 m/a, respectively. After removal of the 17 wrongly unwrapped Sentinel-1 InSAR points in the southern tip of the rock glacier, the standard deviation of the velocity difference is 0.25 m/a, while average, minimum, and maximum velocity differences are 0.00 m/a, −1.28 m/a, and 1.50 m/a, respectively.
Further discrepancies can be observed on the edges of the fastest moving parts of the rock glacier front. The scatter plot of the aerial photo matching and Sentinel-1 LOS velocities (Figure 15a) indicates the effect of the different time intervals (three years as compared with six days) and of the satellite look direction. In Figure 15b, we empirically fitted the Sentinel-1 LOS velocities to the aerial photo matching velocities by scaling them with a factor of −1.23 in order to maximize the one-to-one match and account, therefore, for these two effects. After scaling, the standard deviation of the velocity difference for the 2237 coincident measurement points is 0.30 m/a, while average, minimum and maximum velocity differences are 0.01 m/a, −2.09 m/a, and 2.84 m/a, respectively. After removal of the 17 wrongly unwrapped Sentinel-1 InSAR points in the southern tip of the rock glacier, the standard deviation of the velocity difference is 0.25 m/a, while average, minimum, and maximum velocity differences are 0.00 m/a, −1.28 m/a, and 1.50 m/a, respectively.

SAR Offset Tracking
Delaloye at al. [36] investigated the accuracy of SAR offset tracking for ice surface velocity estimation in various aspects, including a formal description of the error terms, matching on stable ground, comparison against results from SAR image data of equal or better resolution, and groundbased measurements from GNSS. They estimated the reliability of the cross-correlation algorithm to return coregistration parameters in the order of 1/10th of a SAR image pixel. This corresponds for the TerraSAR-X and Cosmo-SkyMed data of our study (Table 1)

SAR Offset Tracking
Delaloye at al. [36] investigated the accuracy of SAR offset tracking for ice surface velocity estimation in various aspects, including a formal description of the error terms, matching on stable ground, comparison against results from SAR image data of equal or better resolution, and ground-based measurements from GNSS. They estimated the reliability of the cross-correlation algorithm to return coregistration parameters in the order of 1/10th of a SAR image pixel. This corresponds for the TerraSAR-X and Cosmo-SkyMed data of our study (Table 1) Figure 16. These results clearly point to the lower spatial resolution of TerraSAR-X offset tracking with respect to matching of aerial optical images, with large discrepancies on the edges of the fastest moving parts of the rock glacier. The scatter plot of the aerial photo matching and TerraSAR-X velocities (Figure 17) also indicates a bias of the offset tracking results, which are generally lower than those from the matching of aerial images as a result of the larger cross-correlation window size used with SAR images. The standard deviation of the velocity difference for the 2197 coincident measurement points is 0.34 m/a, while average, minimum, and maximum velocity differences are     Figure 18a, while the scatter plot of GNSS and Cosmo-SkyMed velocities is presented in Figure 18b. For the eight coincident measurement points, the standard deviation of the velocity difference is 1.00 m/a, while average, minimum and maximum velocity differences are 0.40 m/a, −1.36 m/a, and 1.86 m/a, respectively. In Figure 18a,b we also observed that the deviation between GNSS and Cosmo-SkyMed velocities increases for larger values. In summary, we note that rock glaciers in the Swiss Alps are rather small objects (e.g., 0.5 km long and 100 to 200 m width) and offset tracking is at the limit of its applicability even with very high-resolution SAR images with a resolution of about 2 m. The measurement uncertainty is, thus, larger than assessed over fast-flowing (e.g., >300 m/a) and large (e.g., >10 km) Arctic glaciers over shorter (e.g., few days) time periods [36]. For the TerraSAR-X images used for offset tracking over two years with image matching windows of 64 × 64 pixels, corresponding to a resolution of about 125 meters on the ground, the assessed measurement uncertainty over the Distelhorn rock glacier is about 0.3 m/a. For the Cosmo-SkyMed images used for offset tracking over one year with image matching windows of 64 × 64 pixels over the Tsarmine rock glacier, the assessed measurement uncertainty is in the order of 1.0 m/a. The Tsarmine rock glacier is only 150 m in width as compared with the width of about 300 m of the Distelhorn rock glacier, and the performance of SAR offset tracking is, therefore, well expected to be worse.

Discussion
With Sentinel-1, satellite SAR images that enable interferometry are nowadays regularly acquired worldwide. Therefore, this mission provides consistent time series of rock glacier velocities every six days over Europe and Greenland and every 12 days over other mountainous regions, including the Andes of South America. The estimated accuracy of the Sentinel-1 InSAR measurements is in the order of 0.2 m/a. Typical lower and upper limits of detection for six days data are in the order of 0.4 m/a (i.e., 6 mm or 1 mm/day) and 2 m/a (i.e., 2π or 2.8 cm), respectively. Monitoring the kinematics of rock glaciers with Sentinel-1 SAR interferometry is, however, limited by the spatial resolution of the SAR data of about 15 m on the ground for a multi-looking factor of 4 pixels in range and 1 pixel in azimuth. It is, therefore, essential to select a representative point over the rock glacier, where the spatial variability of the motion around is low, in order to extract a meaningful time series of motion. In addition, Sentinel-1, as all other SAR missions, suffers in rugged terrain from incomplete spatial coverage due to layover and shadow and with InSAR the sensitivity to motion is restricted to the LOS. For our analyses, we projected, therefore, the InSAR LOS motion along the maximum slope direction. In this contribution, we demonstrate the potential of the Sentinel-1 mission for monitoring rock glacier movement over three typical rock glaciers in the Swiss Alps, one on Qeqertarsuaq in Western Greenland, and one in the Andes.
Stacks of very high-resolution SAR images from TerraSAR-X and Cosmo-SkyMed, regularly acquired every summer between 2008 and 2017 over the Western Swiss Alps, were analyzed with InSAR and offset tracking in order to extend the observation period of our study. Very highresolution X-band SAR data can be employed over rock glaciers using both InSAR and SAR offset tracking. In the former case, the estimated accuracy is in the order of 0.1 m/a, the upper limit of detection is in the order of 2 m/a, and the ground resolution is in the order of 6 m (for a 3 × 3 multilooking factor). In the latter case, the estimated accuracy is in the order of 0.3 m/a for a time interval In summary, we note that rock glaciers in the Swiss Alps are rather small objects (e.g., 0.5 km long and 100 to 200 m width) and offset tracking is at the limit of its applicability even with very high-resolution SAR images with a resolution of about 2 m. The measurement uncertainty is, thus, larger than assessed over fast-flowing (e.g., >300 m/a) and large (e.g., >10 km) Arctic glaciers over shorter (e.g., few days) time periods [36]. For the TerraSAR-X images used for offset tracking over two years with image matching windows of 64 × 64 pixels, corresponding to a resolution of about 125 meters on the ground, the assessed measurement uncertainty over the Distelhorn rock glacier is about 0.3 m/a. For the Cosmo-SkyMed images used for offset tracking over one year with image matching windows of 64 × 64 pixels over the Tsarmine rock glacier, the assessed measurement uncertainty is in the order of 1.0 m/a. The Tsarmine rock glacier is only 150 m in width as compared with the width of about 300 m of the Distelhorn rock glacier, and the performance of SAR offset tracking is, therefore, well expected to be worse.

Discussion
With Sentinel-1, satellite SAR images that enable interferometry are nowadays regularly acquired worldwide. Therefore, this mission provides consistent time series of rock glacier velocities every six days over Europe and Greenland and every 12 days over other mountainous regions, including the Andes of South America. The estimated accuracy of the Sentinel-1 InSAR measurements is in the order of 0.2 m/a. Typical lower and upper limits of detection for six days data are in the order of 0.4 m/a (i.e., 6 mm or 1 mm/day) and 2 m/a (i.e., 2π or 2.8 cm), respectively. Monitoring the kinematics of rock glaciers with Sentinel-1 SAR interferometry is, however, limited by the spatial resolution of the SAR data of about 15 m on the ground for a multi-looking factor of 4 pixels in range and 1 pixel in azimuth. It is, therefore, essential to select a representative point over the rock glacier, where the spatial variability of the motion around is low, in order to extract a meaningful time series of motion. In addition, Sentinel-1, as all other SAR missions, suffers in rugged terrain from incomplete spatial coverage due to layover and shadow and with InSAR the sensitivity to motion is restricted to the LOS. For our analyses, we projected, therefore, the InSAR LOS motion along the maximum slope direction. In this contribution, we demonstrate the potential of the Sentinel-1 mission for monitoring rock glacier movement over three typical rock glaciers in the Swiss Alps, one on Qeqertarsuaq in Western Greenland, and one in the Andes.
Stacks of very high-resolution SAR images from TerraSAR-X and Cosmo-SkyMed, regularly acquired every summer between 2008 and 2017 over the Western Swiss Alps, were analyzed with InSAR and offset tracking in order to extend the observation period of our study. Very high-resolution X-band SAR data can be employed over rock glaciers using both InSAR and SAR offset tracking. In the former case, the estimated accuracy is in the order of 0.1 m/a, the upper limit of detection is in the order of 2 m/a, and the ground resolution is in the order of 6 m (for a 3 × 3 multi-looking factor). In the latter case, the estimated accuracy is in the order of 0.3 m/a for a time interval of two years and 0.6 m/a for a time interval of one year. Displacements of more than 6 m/a could be successfully detected with SAR offset tracking, but the spatial resolution is poor (~125 m), and therefore detailed spatial variabilities of motion cannot be captured.
Despite analyzing a limited number of rock glaciers, our study clearly indicates large spatial variability in rock glacier kinematics within the study regions. In [4], speed variations within individual rock glaciers are discussed in more detail and it was concluded that their kinematics appear to be related to the local topography in particular. The study, in [10], also observed large variations of rock glacier velocities on Qeqertarsuaq, with values ranging from 0.1 to 1 m/a. We also detected on all analyzed rock glaciers (Figures 3, 5, 7, 9 and 11) a seasonal variability of the rate of motion, with higher velocities at the end of the summer. This observation is in-line with in situ measurements, also pointing to seasonal variability of the rock glacier's kinematics [14,16,23]. During the last decade, in situ data also showed that rock glaciers responded almost synchronously to inter-annual and decennial ground temperature changes. With the limited observations of our study we confirmed this trend at the Tsarmine rock glacier ( Figure 5) and found an apparent change of the seasonal variability at the Distelhorn rock glacier, since 2016, over its eastern front (Figure 3a). In order to further study trends in rock glacier kinematics using InSAR to possibly confirm acceleration, longer time series of motion from Sentinel-1 InSAR are, however, necessary.

Conclusions and Outlook
Our results in three different regions worldwide (European Alps, Qeqertarsuaq in Western Greenland, and Andes of South America) demonstrate the good performance of high-resolution Sentinel-1 data for the monitoring of rock glacier kinematics. Coherent interferograms over six or 12 days are available not only for most of the snow-free acquisitions, but also in mid-winter by stable dry snow conditions. A typical annual cycle of rock glacier velocities with higher values in autumn and lower values in spring could be observed with an estimated accuracy on the order of 0.2 m/a. In this contribution, we selected representative rock glaciers for Sentinel-1 InSAR analyses. Our next step is to investigate which and how many rock glaciers per region can be analyzed with Sentinel-1 InSAR for more general analyses. A long-term analysis of the Sentinel-1 InSAR time series can possibly lead to observed changes in rock glacier motion as indicators of general mountain permafrost conditions. Stacks of very high-resolution SAR images from TerraSAR-X and Cosmo-SkyMed analyzed using both InSAR and offset tracking were used to complement the Sentinel-1 InSAR analyses. In order to be acquired, however, very high-resolution SAR data must be programmed in advance and their use is, thus, limited. In Switzerland, for example, we only program TerraSAR-X data during the summer months for specific regions and Cosmo-SkyMed data are only available at the border to Italy. Over other regions worldwide, acquired very high-resolution SAR images are much more sparse. Studies of active rock glaciers would strongly benefit from having a much larger number of interferograms at very high-spatial resolution (i.e., TerraSAR-X or Cosmo-SkyMed) available with short repeat time intervals.
Facing the importance of documenting the changes occurring in the transfer rate of frozen debris over mountain slopes, the Swiss permafrost observation network PERMOS [18] has included a kinematics tier in its monitoring strategy, in addition to the observation of permafrost temperature and active layer trends. This is, however, not yet the case in other mountain regions or in the Global Terrestrial Network for Permafrost GTN-P [85], despite an increasing number of publications dedicated to this specific emerging geomorphological response to the climate warming [3,14,17,86,87]. In addition, inventories of rock glaciers and monitoring of rock glacier velocities is not explicitly mentioned by the Global Climate Observing System (GCOS) of the World Meteorological Organization (WMO) as being an essential climate variable (ECV) associated parameter, despite the fact that monitoring rock glacier velocities at the regional scale provides information on the impact of climate change on mountain slope stability, and rock glacier monitoring builds up a unique validation dataset of climate models for mountain regions, where direct permafrost (thermal state) measurements are scarce. An Action Group of the International Permafrost Association (IPA) is intending to promote the integration of permafrost creep rates (rock glacier kinematics) as a new parameter associated with the ECV Permafrost within the GCOS [88], characterizing the evolution of mountain permafrost at the global scale. In this context, satellite SAR data can complement in situ collections of rock glacier kinematics and expand, with a degree of independence, in situ networks.
Author Contributions: T.S., R.D., and A.K. designed the experiments; T.S., R.C., and N.J. processed the satellite SAR images; A.K. processed the aerial optical images; C.B. and R.D. contributed to the discussion and validation in the Western Swiss Alps; N.J. and E.M. contributed to the discussion in Qeqertarsuaq; X.B. and L.S. contributed to the discussion in the Tapado/Agua Negra Region; T.S. led the writing of the paper; all authors analyzed the results and contributed to the writing of the paper. All authors have read and agreed to the published version of the manuscript.