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1000 Titel
  • Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada
1000 Autor/in
  1. Sykes, John |
  2. Toft, Håvard |
  3. Haegeli, Pascal |
  4. Statham, Grant |
1000 Verlag
  • Copernicus Publications
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-03-20
1000 Erschienen in
1000 Quellenangabe
  • 24(3):947-971
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.5194/nhess-24-947-2024 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:p>Abstract. The Avalanche Terrain Exposure Scale (ATES) is a system for classifying mountainous terrain based on the degree of exposure to avalanche hazard. The intent of ATES is to improve backcountry recreationist's ability to make informed risk management decisions by simplifying their terrain analysis. Access to ATES has been largely limited to manually generated maps in high-use areas due to the cost and time to generate ATES maps. Automated ATES (AutoATES) is a chain of geospatial models which provides a path towards developing ATES maps on large spatial scales for relatively minimal cost compared to manual maps. This research validates and localizes AutoATES using two ATES benchmark maps which are based on independent ATES maps from three field experts. We compare the performance of AutoATES in two study areas with unique snow climate and terrain characteristics: Connaught Creek in Glacier National Park, British Columbia, Canada, and Bow Summit in Banff National Park, Alberta, Canada. Our results show that AutoATES aligns with the ATES benchmark maps in 74.5 % of the Connaught Creek study area and 84.4 % of the Bow Summit study area. This is comparable to independently developed manual ATES maps which on average align with the ATES benchmark maps in 76.1 % of Connaught Creek and 84.8 % of Bow Summit. We also compare a variety of DEM types (lidar, stereo photogrammetry, Canadian National Topographic Database) and resolutions (5–26 m) in Connaught Creek to investigate how input data type affects AutoATES performance. Overall, we find that DEM resolution and type are not strong indicators of accuracy for AutoATES, with a map accuracy of 74.5 % ± 1 % for all DEMs. This research demonstrates the efficacy of AutoATES compared to expert manual ATES mapping methods and provides a platform for large-scale development of ATES maps to assist backcountry recreationists in making more informed avalanche risk management decisions. </jats:p>
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  1. https://frl.publisso.de/adhoc/uri/U3lrZXMsIEpvaG4=|https://frl.publisso.de/adhoc/uri/VG9mdCwgSMOldmFyZA==|https://frl.publisso.de/adhoc/uri/SGFlZ2VsaSwgUGFzY2Fs|https://frl.publisso.de/adhoc/uri/U3RhdGhhbSwgR3JhbnQ=
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1000 Label
1000 Förderer
  1. Natural Sciences and Engineering Research Council of Canada |
1000 Fördernummer
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1000 Förderprogramm
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1000 Dateien
1000 Förderung
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    1000 Förderer Natural Sciences and Engineering Research Council of Canada |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6480773.rdf
1000 Erstellt am 2024-05-23T16:45:06.846+0200
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1000 Zuletzt bearbeitet 2024-05-27T11:48:42.045+0200
1000 Objekt bearb. Mon May 27 11:48:42 CEST 2024
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