Description: Within ESA’s CryoSat-2 calibration and validation program (CryoVEx) an airborne campaign was carried out in the blue ice area in the vicinity of Schirmacher oasis, Dronning Maud Land, Antarctica in 2008. POLAR 5, the Alfred-Wegener-Institute’s research aircraft, carried the ESA airborne Ku-band SAR interferometric radar altimeter (ASIRAS) and a laser scanner during the CryoVEx campaign. In the blue ice area, partly covered with snow patches, a dense grid of 30 km x 40 km with a line spacing of 1 km was measured. Here, we present results of the comparisons of the final SAR processed ASIRAS elevations with the laser scanner elevation model. We will show the influence of snow patches on and the accuracy of the ASIRAS derived surface elevations by using the laser scanner DEM as reference. Furthermore, the derived Ku-band penetration depths and the thickness of the snow patches, derived from the ASIRAS data, are compared with the radar backscatter of a TerraSAR-X scene, acquired at the same time when the campaign took place. Our results show that Ku-band radar penetrates through the snow, while the snow patches do not affect the derived ASIRAS surface elevations. In contrast the radar backscatter of TerraSAR-X shows a strong correlation of the thickness of the snow patches. The results of this study highlight the need of careful waveform processing/re-tracking and though will contribute to improved CryoSat-2 elevation products.

Description: In response to increasing Arctic temperatures, ice-rich permafrost landscapes are undergoing rapid changes. In permafrost lowlands, polygonal ice wedges are especially prone to degradation. Melting of ice wedges results in deepening troughs and the transition from low-centered to high-centered ice-wedge polygons. This process has important implications for surface hydrology, as the connectivity of such troughs determines the rate of drainage for these lowland landscapes. In this study, we present a comprehensive, modular, and highly automated workflow to extract, to represent, and to analyze remotely sensed ice-wedge polygonal trough networks as a graph (i.e., network structure). With computer vision methods, we efficiently extract the trough locations as well as their geomorphometric information on trough depth and width from high-resolution digital elevation models and link these data within the graph. Further, we present and discuss the benefits of graph analysis algorithms for characterizing the erosional development of such thaw-affected landscapes. Based on our graph analysis, we show how thaw subsidence has progressed between 2009 and 2019 following burning at the Anaktuvuk River fire scar in northern Alaska, USA. We observed a considerable increase in the number of discernible troughs within the study area, while simultaneously the number of disconnected networks decreased from 54 small networks in 2009 to only six considerably larger disconnected networks in 2019. On average, the width of the troughs has increased by 13.86%, while the average depth has slightly decreased by 10.31%. Overall, our new automated approach allows for monitoring ice-wedge dynamics in unprecedented spatial detail, while simultaneously reducing the data to quantifiable geometric measures and spatial relationships.