Yedoma—extremely ice-rich permafrost with massive ice wedges formed in extensive regions in northern Siberia, Alaska, and northwest Canada during the Late Pleistocene [1
]—is vulnerable to thawing and degradation under climate warming. The thawing of ice-rich permafrost results in widespread thermokarst development, reshaping the landscape into Yedoma uplands and interconnected drained thermokarst lake [3
]. Due to its syngenetic formation history, Yedoma deposits store large amounts of organic carbon which are vulnerable to mobilization upon thaw [5
]. Therefore, Yedoma degradation contributes to climate warming through the release of greenhouse gases from microbial decomposition of thawed organic carbon [7
Thermokarst and associated thaw subsidence are key land surface indicators for permafrost degradation processes [9
]. To study surface elevation changes over ice-rich Yedoma, associated with the freeze and thaw cycling processes, is of importance to understand the response of Yedoma uplands to surface disturbance and/or climatic changes. Generally, the ground surface subsides/uplifts seasonally as a result of the volumetric contraction/expansion due to the moisture phase transition between the frozen and unfrozen soil in the active layer. In addition, upon surface disturbance, such as massive snowfall or precipitation, the volumetric ice content exceeds the total soil pore volume in freeze season, i.e., the formation of excess ground ice [10
]. If the excess meltwater upon the thawing of excess ground ice in the uppermost permafrost layer is well drained, the ground experiences additional secular subsidence. Otherwise, the excess meltwater pools up and thus trigger the formation of the thermokarst landforms. The dynamic processes between the active layer and underlying ice-rich Yedoma deposits further affect soil moisture content and vegetation growth, leading to changes in ground thermal regime and the energy exchanges between the land surface and the atmosphere [11
]. These interactions potentially provide further feedbacks to surface elevation changes.
Interferometric Synthetic Aperture Radar (InSAR) is a technique to quantify surface elevation changes independent of weather and light conditions, which is an ideal precondition for such studies in Arctic permafrost regions. The basic principle of InSAR for measuring deformation is to compare the phase of two complex Synthetic Aperture Radar (SAR) signals that were acquired from slightly different positions at different times. The phase differences are used to measure the displacements along the line of sight (LOS) between the repeat SAR acquisitions. InSAR measurements have been frequently used to measure ground surface subsidence for geophysical researches, such as deformation of volcanoes, earthquake-generated displacements, landslides, and urban studies [12
The Sentinel-1A/B constellation is a new generation of two C-band SAR satellites, launched on 3 April 2014 and 25 April 2016, respectively. The main advancement of Sentinel-1 is the new imaging technique, i.e., the Terrain Observation by Progressive Scans (TOPS) [17
]. This technique allows the Sentinel-1 SAR images to cover large footprints (about 250 km across the orbit track) by three overlapping sub-swaths. Sentinel-1 measurements characterize with frequent revisit time (regular revisit time is 12 days; shortest is six days if both Sentinel-1A and -1B images are acquired). Furthermore, the orbit configuration of Sentinel-1 results in a spatial baseline for InSAR of about 150 m [18
]. The European Space Agency (ESA), operated Global Monitoring for Environment and Security (GMES) space component program, provides all the Sentinel-1A/B archives at no cost to all users.
However, the availability of suitable SAR images for InSAR measurements not only relies on the revisit time of SAR missions but also highly depends on the interferometric coherence. Interferometric coherence, the similarity between the two SAR signals, is a key indicator of the quality of InSAR measurements. Generally, high interferometric coherence indicates that the phase observations contain useful information and are less affected by noise. The source of decorrelation (loss of coherence) is mainly related to the variation of geometric configuration between the repeat-pass satellites, the temporal variation in the physical features of the ground surface, and the thermal noise [19
]. The geometric decorrelation is related to the satellite configurations (i.e., incident angle, wavelength, spatial resolution, and satellite to ground distance) and the spatial baseline between repeat satellite observations. Taking the maximum spatial baseline (about 150 m) as an example, the spatial correlation term is about 0.96, suggesting that the geometric decorrelation for Sentinel-1 InSAR can be ignored [18
]. Hence, the dominant decorrelation source is the temporal decorrelation related to surface processes, mainly including soil moisture variation, freezing and thawing processes, and vegetation phenology changes and succession.
The space-borne X-band, C-band, and L-band repeat-pass SAR missions prior to the Sentinel-1A/B satellites have been used to monitor seasonal and inter-annual thaw subsidence in permafrost regions [21
]. However, these InSAR measurements (C- and L-band) only provide a limited number of repeat images, and hardly resolve the temporal evolution of seasonal thaw subsidence and/or inter-annual variabilities. TerraSAR-X, the X-band repeat-pass SAR mission, provides frequent measurements (regular revisit time is 11 days). TerraSAR-X InSAR measurements have a high sensitivity to changes at the ground surface [25
]. Thus, the interferometric coherence of X-band data drops rapidly through time in tundra lowlands, which limits the suitability of X-band repeat-pass SAR to detect thaw subsidence [28
]. The Sentinel-1 InSAR measurements with relatively high temporal resolution provide an excellent opportunity to study the suitability of C-band data for permafrost elevation changes in a detailed manner.
The aim of this study is to demonstrate the capability of Sentinel-1 InSAR measurements to detect elevation changes over Yedoma uplands in an Arctic permafrost region. We use the InSAR approach to quantify the seasonal and inter-annual elevation changes over ice-rich Yedoma uplands on Sobo-Sise Island, Lena Delta. To understand the spatial patterns of seasonal subsidence, we analyze the correlation between seasonal thaw subsidence and Yedoma elevation. To account for the temporal evolution of inter-annual elevation changes, we also analyze the relationship between the inter-annual elevation changes and air temperature.