Extracting recent short-term glacier velocity evolution over southern Alaska and the Yukon from a large collection of Landsat data
2019
Abstract. The measurement of glacier
velocity fields using repeat satellite imagery has become a standard method
of cryospheric research. However, the reliable discovery of important glacier
velocity variations on a large scale is still problematic because time series
span different time intervals and are partly populated with erroneous
velocity estimates. In this study we build upon existing glacier velocity
products from the GoLIVE dataset ( https://nsidc.org/data/golive , last
access: 26 February 2019) and compile a multi-temporal stack of velocity data
over the Saint Elias Mountains and vicinity. Each layer has a time separation
of 32 days, making it possible to observe details such as within-season
velocity change over an area of roughly 150 000 km 2 . Our methodology
is robust as it is based upon a fuzzy voting scheme applied in a discrete
parameter space and thus is able to filter multiple outliers. The
multi-temporal data stack is then smoothed to facilitate interpretation. This
results in a spatiotemporal dataset in which one can identify short-term
glacier dynamics on a regional scale. The goal is not to improve accuracy or
precision but to enhance extraction of the timing and location of ice flow
events such as glacier surges. Our implementation is fully automatic and the
approach is independent of geographical area or satellite system used. We
demonstrate this automatic method on a large glacier area in Alaska and
Canada. Within the Saint Elias and Kluane mountain ranges, several surges and
their propagation characteristics are identified and tracked through time, as
well as more complicated dynamics in the Wrangell Mountains.
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