SkiVis: Visual Exploration and Route Planning in Ski Resorts

Optimal ski route selection is a challenge based on a multitude of factors, such as the steepness, compass direction, or crowdedness. The personal preferences of every skier towards these factors require individual adaptations, which aggravate this task. Current approaches within this domain do not...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2024-01, Vol.30 (1), p.869-879
Main Authors: Rauscher, Julius, Buchmuller, Raphael, Keim, Daniel A., Miller, Matthias
Format: Article
Language:English
Subjects:
Compass
Geographic Visualization
Geospatial analysis
Navigation
Planning
Resorts & spas
Route planning
Route selection
Routing
Ski resorts
Skiing
Slopes
Snow
Task analysis
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Summary:Optimal ski route selection is a challenge based on a multitude of factors, such as the steepness, compass direction, or crowdedness. The personal preferences of every skier towards these factors require individual adaptations, which aggravate this task. Current approaches within this domain do not combine automated routing capabilities with user preferences, missing out on the possibility of integrating domain knowledge in the analysis process. We introduce SkiVis, a visual analytics application to interactively explore ski slopes and provide routing recommendations based on user preferences. In collaboration with ski guides and enthusiasts, we elicited requirements and guidelines for such an application and propose different workflows depending on the skiers' familiarity with the resort. In a case study on the resort of Ski Arlberg, we illustrate how to leverage volunteered geographic information to enable a numerical comparison between slopes. We evaluated our approach through a pair-analytics study and demonstrate how it supports skiers in discovering relevant and preference-based ski routes. Besides the tasks investigated in the study, we derive additional use cases from the interviews that showcase the further potential of SkiVis, and contribute directions for further research opportunities.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2023.3326940