Abstract
AbstractFinely resolved geodetic data provide an opportunity to assess the extent and morphology of crevasses and their change over time. Crevasses have the potential to bias geodetic measurements of elevation and mass change unless they are properly accounted for. We developed a framework that automatically maps and extracts crevasse geometry and masks them where they interfere with surface mass-balance assessment. Our study examines airborne light detection and ranging digital elevation models (LiDAR DEMs) from Haig Glacier, which is experiencing a transient response in its crevassed upper regions as the glacier thins, using a self-organizing map algorithm. This method successfully extracts and characterizes ~1000 crevasses, with an overall accuracy of 94%. The resulting map provides insight into stress and flow conditions. The crevasse mask also enables refined geodetic estimates of summer mass balance. From differencing of September and April LiDAR DEMs, the raw LiDAR DEM gives a 9% overestimate in the magnitude of glacier thinning over the summer: −5.48 m compared with a mean elevation change of −5.02 m when crevasses are masked out. Without identification and removal of crevasses, the LiDAR-derived summer mass balance therefore has a negative bias relative to the glaciological surface mass balance.
Highlights
Glacier crevasses are fractures that form from the failure of ice under tension as it flows around obstacles or is subject to a divergent velocity field
One-meter resolution is a suitable pixel size for detailed study of the larger crevasse features, which are tens of meters in length, but some small cracks may not be detected in the light detection and ranging (LiDAR) data or captured in the digital elevation models (DEMs)
An automatic methodology for mapping and geometric analysis of crevasses based on self-organizing maps (SOM) is described in the current study
Summary
Glacier crevasses are fractures that form from the failure of ice under tension as it flows around obstacles or is subject to a divergent velocity field (e.g. through higher downstream ice speeds). Crevasses appear when local strain exceeds a critical tensional strength threshold (Vaughan, 1993), which effectively pulls a glacier apart (Hargitai and Kereszturi, 2015) Their orientation is related to the regional stress regime and flow direction (Harper and others, 1998; Hambrey and Lawson, 2000). Crevasses are ubiquitous on glaciers on Earth, as well as extraterrestrial bodies such as ice-rich surfaces on Mars (Hubbard and others, 2014; Adeli and others, 2016), and are suggested to be on Pluto (Howard and others, 2017) They occur at scales from centimeters to tens of kilometers, individually or in groups that form diverse patterns such as chessboards (Hargitai and Kereszturi, 2015). Automated detection and mapping of existing and emerging crevasses is required for glaciological research; automated crevasse mapping would improve the safety of travel on glaciers and ice sheets
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