A random forest approach to quality-checking automatic snow-depth sensor measurements
A random forest approach to quality-checking automatic snow-depth sensor measurements
About this item
Full title
Author / Creator
Publisher
Katlenburg-Lindau: Copernicus GmbH
Journal title
Language
English
Formats
Publication information
Publisher
Katlenburg-Lindau: Copernicus GmbH
Subjects
More information
Scope and Contents
Contents
State-of-the-art snow sensing technologies currently provide an unprecedented amount of data from both remote sensing and ground sensors, but their assimilation into dynamic models is bounded to data quality, which is often low – especially in mountain, high-elevation, and unattended regions where snow is the predominant land-cover feature. To maxi...
Alternative Titles
Full title
A random forest approach to quality-checking automatic snow-depth sensor measurements
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_d07052c7a52340b9be5376070288f470
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d07052c7a52340b9be5376070288f470
Other Identifiers
ISSN
1994-0424,1994-0416
E-ISSN
1994-0424,1994-0416
DOI
10.5194/tc-17-5317-2023
