Articles | Volume 25, issue 3
https://doi.org/10.5194/nhess-25-1255-2025
https://doi.org/10.5194/nhess-25-1255-2025
Research article
 | 
02 Apr 2025
Research article |  | 02 Apr 2025

Development of operational decision support tools for mechanized ski guiding using avalanche terrain modeling, GPS tracking, and machine learning

John Sykes, Pascal Haegeli, Roger Atkins, Patrick Mair, and Yves Bühler

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2024-147', Anonymous Referee #1, 18 Sep 2024
    • AC1: 'Reply on RC1', John Sykes, 19 Nov 2024
  • RC2: 'Comment on nhess-2024-147', Anonymous Referee #2, 18 Sep 2024
    • AC1: 'Reply on RC1', John Sykes, 19 Nov 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to minor revisions (review by editor) (22 Nov 2024) by Sven Fuchs
AR by John Sykes on behalf of the Authors (05 Jan 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (06 Jan 2025) by Sven Fuchs
AR by John Sykes on behalf of the Authors (15 Jan 2025)
Download
Short summary
We model the decision-making of professional ski guides and develop decision support tools to assist with determining appropriate terrain based on current conditions. Our approach compares a manually constructed Bayesian network with machine learning classification models. The models accurately capture the real-world decision-making outcomes in 85–93 % of cases. Our conclusions focus on strengths and weaknesses of each model and discuss ramifications for practical applications in ski guiding.
Share
Altmetrics
Final-revised paper
Preprint