| Summary: | The western Canadian Arctic is identified as an area of potentially significant global warming. Thawing permafrost, sea level rise, changing sea ice conditions and increased wave activity will result in accelerated rates of coastal erosion and thermokarst activity in areas of ice-rich permafrost. The Yukon Coastal Plain is widely recognized as one of the most ice-rich and thaw-sensitive areas in the Canadian Arctic. In particular, Herschel Island displays extensive coastal thermokarst. Retrogressive thaw slumps are a common thermokarst landform along the Herschel Island coast that have been increasing in both frequency and extent have in recent years due to increased thawing of massive ground ice and coastal erosion. The volume of sediment and ground ice eroded by retrogressive slump activity and the potential release of climate change related materials like organic carbon, carbon dioxide and methane are largely unknown. The remote setting of Herschel Island, and the Arctic in general, make direct observation of this type of erosion and the analysis of potential climate feedbacks extremely problematic. Remote sensing provides possibly the best solution to this problem. This study looks at two retrogressive thaw slumps located on the western shore of Herschel Island and using stereophotogrammetric methods attempts to (1) develop the first three-dimensional geomorphic analysis of this type of landform, and (2) provide an estimation of the volume of sediment/ground ice eroded through back wasting thermokarst activity. Digital Elevation Models were extracted for the years 1952, 1970 and 2004 and validated using data collected in the field using Kinematic Differential Global Positioning System. Estimates of sediment volumes eroded from retrogressive thaw slumps were found to vary greatly. In one case the total volume of material lost for the 1970–2004 period was approximately 1560000m 3 . The estimated volume of sediment alone was 360000m 3 . The temporal analysis of the DEMs suggest that second generation ...
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