Assessing TanDEM-X-Derived Digital Elevation Models for Monitoring Rapid Permafrost Thaw: A Case Study in the Mackenzie River Delta
Creators: name: Maier, Kathrin
name: Bernhard, Philipp
name: Hajnsek, Irena
Publisher: name: ETH Zurich
Year: 2023
Subjects: Permafrost
Retrogressive Thaw Slumps
DEM
info:eu-repo/classification/ddc/550
Earth sciences

description: Permafrost is a common characteristic of Arctic landscapes, where it refers to ground that remains at or below 0 °C for a duration of at least two consecutive years. Permafrost underlies approximately 15 % of the landmass in the Northern Hemisphere and is becoming more susceptible to rapid thawing as the climate continues to warm (Obu et al. 2019). When ice-rich permafrost thaws it can alter the surface characteristics of a landscape which is commonly referred to as thermokarst. Retrogressive Thaw Slumps (RTS) are emerging as one of the most dynamic types of thermokarst, varying strongly in shape and thawing behavior. The prevalence and distribution of rapid thaw on a pan-Arctic scale are not well understood and so is its potential contribution in the Arctic carbon-climate feedback (Kokelj et al. 2009). High-resolution Digital Elevation Models (DEMs) are a valuable tool for monitoring surface characteristics of thermokarst features and track changes over time, which in turn improves our understanding of large-scale landscape changes and their implications for hydrology, biochemistry, permafrost stability, and hazard risk management (Jorgensson and Grosse 2016). To derive these DEMs, a range of techniques are employed, including ground-based and aerial LiDAR (e.g., Patton et al. 2021), optical stereo-imagery from airborne (e.g., Lim et al. 2020) and satellite platforms (e.g., Günther et al. 2015). The high-resolution ArcticDEM has been used to supplement optical satellite data in monitoring highly dynamic thermokarst features such as RTS towards the pan-Arctic scale (Yang et al. 2023). However, these methods are subject to spatial coverage and availability constraints, or data quality issues and data gaps due to limitations such as cloud cover, seasonal snow, vegetation, and illumination conditions for passive optical sensors. Another high-resolution DEM covering the Arctic landscape has been available with the start of the TanDEM-X satellite in 2010, forming together with the TerraSAR-X satellite the TanDEM-X constellation, a bistatic single-pass radar system. The temporal, spatial and vertical resolution of the TanDEM-X mission (10-12 m spatial resolution and approx. 2 m vertical accuracy over Arctic regions) merits investigation for a comprehensive monitoring of rapid permafrost thaw and directly retrieve information about volumetric change rates and thus carbon mobilization. This approach has already been successfully applied to single-pass InSAR-based time-series DEM analysis to detect and quantify volumetric change rates and potential carbon mobilization of RTSs in several test sites in the Arctic permafrost region (Bernhard et al. 2020, Bernhard et al. 2022a, Bernhard et al. 2022b). Uncertainties that still remain include the potential error in the volumetric change rate estimation due to viewing geometry of the SAR sensor, the assumption of complete penetration of the dry winter snowpack of the radar waves, as well as systematic differences between wave polarizations with respect to penetration of snow and vegetation. In this paper we present the learnings from a time-series TanDEM-X case study in the Mackenzie River Delta that addresses the pending uncertainties when applying TanDEM-X derived DEMs to RTS monitoring. Our study involves a general analysis of the produced DEM accuracy for Arctic permafrost regions, as well as targeted investigations at known RTS locations. The accuracies of the generated DEMs are compared with the high-resolution DEM from a LiDAR campaign (Anders et al. 2018) and the ArcticDEM products to improve the understanding of the underlying accuracies. Potential discrepancies in height accuracies due to viewing geometry of the SAR sensor are assessed through the comparison of DEMs generated from TanDEM-X observations with different orbit directions. Furthermore, the impact of snow and vegetation cover on the penetration of the radar waves to the ground and resulting height discrepancies is investigated. For this investigation we choose the upland region to the east of the Mackenzie River Delta which is located in the western Canadian Arctic and is characterized by a subarctic climate. The region is dominated by tundra vegetation and contains large amounts of ground ice. Studies found a high concentration of relatively small RTSs with head wall heights of 2-10 meters (Kokelj et al. 2013). In addition to the global TanDEM-X bistatic single-pol observations (availability in Arctic permafrost landscapes: 2010/11/12 and 2016/17), additional observations with a variety of observation properties are available for the study region: Bistatic dual-polarization observations are available in 2018/19, as well as high temporal resolution time-series (11-day repeat pass) during multiple periods between 2011 and 2022. The data from the TanDEM-X Science Phase in 2015 offers high baselines yielding vertical accuracies on sub-meter level. All observations with height of ambiguities greater than 80 meters are removed ensuring acceptable vertical accuracy needed for RTS detection. DEMs are generated with standard InSAR techniques from the pairs of TanDEM-X images and are differenced on multiple timescales. 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