Snow depth mapping in the Alps: Merging of in situ and remotely-sensed data
Nando Foppa, Andreas Stoffel and Roland Meister
Abstract
The Swiss
Federal Institute for Snow and Avalanche Research in Davos (SLF) publishes
daily snow and avalanche information including snow depth maps on a spatial
resolution of 1x1 km2
for Switzerland. These maps are generated using a spatial interpolation
technique based on snow station measurements. Although the station network has
become denser over the past years, several regions do not contribute well to
the network. The U.S. National Oceanic and Atmospheric Administration (NOAA)
Advanced Very High Resolution Radiometer (AVHRR) sensor is used to improve the
information on snow-covered ground. The fusion of point measurements with
small-scale remote sensing data leads to an improved area-wide snow
information. The presented merging technique based on virtual snow stations is
applied for a case study on the Swiss Alps on 4 January 2005. The combination
technique is a new approach and the resulting nation-wide snow depth maps show
a significant improvement compared to the conventional interpolation with a
more accurate snow – no snow borderline. The interpolation method seems to be
sensitive to an accurate snow - no snow classification of the satellite data. The
preliminary results are very promising and a near-real time application is
already in operational use. Ongoing work is concentrating on the validation of
the snow cover maps and improvements to the spatial interpolation method.
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History
Submitted: 23 Feb 2005
Revised: 11 Aug 2005
Accepted: 26 Aug 2005
Citation
Foppa N, A Stoffel & R Meister, 2005.
Snow depth mapping in the Alps: Merging of in situ and remotely-sensed data. EARSeL eProceedings, 4(1), 119-129
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ISSN 1729-3782
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