Abstract
Mapping snow cover (SC) on glaciers at the end of the ablation period provides a possibility
to rapidly obtain a proxy for their equilibrium line altitude (ELA) which in turn is a metric for the
mass balance. Satellite determination of glacier snow cover, derived over large regions, can reveal
its spatial variability and temporal trends. Accordingly, snow mapping on glaciers has been widely
applied using several satellite sensors. However, as glacier ice originates from compressed snow, both
have very similar spectral properties and standard methods to map snow struggle to distinguish snow
on glaciers. Hence, most studies applied manual delineation of snow extent on glaciers. Here we
present an automated tool, named ‘ASMAG’ (automated snow mapping on glaciers), to map SC on
glaciers and derive the related snow line altitude (SLA) for individual glaciers using multi-temporal
Landsat satellite imagery and a digital elevation model (DEM). The method has been developed
using the example of the Ötztal Alps, where an evaluation of the method is possible using field-based
observations of the annual equilibrium line altitude (ELA) and the accumulation area ratio (AAR)
measured for three glaciers for more than 30 years. The tool automatically selects a threshold to map
snow on glaciers and robustly calculates the SLA based on the frequency distribution of elevation bins
with more than 50% SC. The accuracy of the SC mapping was about 90% and the SLA was determined
successfully in 80% of all cases with a mean uncertainty of 19 m. When cloud-free scenes close to
the date of the highest snowline are available, a good to very good agreement of SC ratios (SCR)/SLA
with field data of AAR/ELA are obtained, otherwise values are systematically higher/lower as useful
images were often acquired too early in the summer season. However, glacier specific dierences
are still well captured. Snow mapping on glaciers is impeded by clouds and their shadows or when
fresh snow is covering the glaciers, so that more frequent image acquisitions (as now provided by
Sentinel-2) would improve results.
Keywords: