Landform signature of the Laurentide and Cordilleran ice sheets across Alberta during the last glaciation

• Published in: Canadian Journal of Earth Sciences
• Main Authors: Atkinson, Nigel, Utting, Daniel J., Pawley, Steven M.
• Other Authors: Trenhaile, Alan
• Format: Article in Journal/Newspaper
• Language: English
• Published: Canadian Science Publishing 2014
• Subjects: Ice Sheet
• Online Access: http://dx.doi.org/10.1139/cjes-2014-0112; http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjes-2014-0112; http://www.nrcresearchpress.com/doi/pdf/10.1139/cjes-2014-0112

Government geological survey maps and research publications have portrayed the distribution of glacial landforms associated with the advance and retreat of the Laurentide and Cordilleran ice sheets across Alberta at a local, regional, and continental scale. To date, this information has not been systematically synthesized into a single compilation at a consistent scale. Although this original work provided valuable information to constrain reconstructions of former ice sheet extent, configuration, and flow geometry, its derivation primarily from the interpretation of aerial photographs and the Shuttle Radar Topography Mission 90 m digital elevation model (DEM) may result in methodological inconsistencies and spatial biases. These biases, together with challenges associated with geomorphic mapping in densely forested areas of western and northern Alberta limit the usefulness of previous mapping when applied to inversion-based ice sheet reconstructions, which have specific input data demands. Recently, light detection and ranging (LiDAR) DEMs have become increasingly available throughout Alberta. Hill-shaded imagery of these data provides unprecedented geomorphic detail beneath the forest cover and reveals that that the glacial geomorphology of northern and western Alberta is more complex than previously recognized. In this paper, we describe the methodology and geomorphic criteria used to produce a glacial landform map of Alberta using previously published data, supplemented by comprehensive new analysis of high-resolution (2–25 m) DEMs. These include 306 624 km 2 of LiDAR imagery, with which it is now possible to verify and where necessary augment previous mapping, particularly across areas with a dense forest cover.