Here are a few use cases for this project:

1. Safety Monitoring: This model could be used in ski resorts for real-time monitoring of skiers, enabling authorities to enforce helmet rules and reduce the risk of injury.

2. Sport Event Analysis: During professional ski competitions, this model might provide real-time analysis, identifying which competitors are wearing helmets and potentially categorizing them based on the type or color of their helmets.

3. Development of Smart Cameras: Integrating this model into smart cameras could enable them to automatically identify and focus on skiers with helmets, useful for specific filming or photography needs.

4. Insurance Investigations: Insurance companies might use this model to enhance their investigation process for winter sport accidents and determine if claimants were following safety protocols like wearing a helmet.

5. AI Ski Coaching: This model can be incorporated into an AI-based ski coaching system in which the model identifies if the trainee is wearing a helmet or not, providing real-time feedback, enhancing safety, and providing an all-around learning experience.

This is a video dataset of men and women skiing (giant slalom). [Details] Category: Video / Subjects: Two Japanese skiers in their 20s, a man and a woman / Format: mp4 [Notes] [Shooting Time] 13 minutes 39 seconds
[Shooting Environment] Outdoors (ski resort)
[Shooting Distance/Angle] Simultaneous shooting from two angles

A total of ***** million U.S. Americans went skiing in 2024, which represented a slight increase over the previous year's figure of ***** million. Out of 2024's total, approximately *** million went cross-country skiing specifically, up from *** million in 2023.

A comprehensive dataset containing crowdsourced rankings of nearly all ski resorts worldwide. The dataset includes detailed information on each resort, such as location, snowfall, number of lifts and slopes, total slope length, and vertical drop. The dataset is updated regularly as more votes are collected. Ski Resorts Ranking

Data on 500 ski resorts around the world, including details on their location, prices, slopes, lifts, and seasons, as well as a complementary table with the snow cover around the world for each month of 2022.

This file resorts contain the columns:

ID: Unique identifier for each resort

Resort: Name of the ski & snowboard resort

Latitude: Latitude for the resort's location

Longitude: Longitude for the resort's location

Country: Country in which the resort is located

Continent: Continent in which the resort is located

Price: Ski pass cost for 1 adult for 1 day in the main season (Euro - €)

Season: Normal start and end of the ski season at the resort (note that it allways will depend on the weather and snowfall)

Highest point: Highest mountain point at the resort (meters)

Lowest point: Lowest possible point to ski at the resort (meters)

Beginner slopes: Total length of "children", "blue", and "green" slopes at the resort (km)

Intermediate slopes: Total length of "red" slopes at the resort (km)

Difficult slopes: Total length of "black", "advanced", and "expert" slopes at the resort (km)

Total slopes: Total length of slopes at the resort (km)

Longest run: Longest possible continuous run at the ski resort (km)

Snow cannons: Total amount of snow cannons at the resort

Surface lifts: Total number of surface lifts, including T-bar, Sunkidslift, Rope lifts and people mover

Chair lifts: Total number of chair lifts

Gondola lifts: Total number of gondola lifts, including Gondola, Train lifts, Funicular, Combined gondola and chairlifts, Helicopter lifts, Snowcats and Aerial tramways

Total lifts: Total number of lifts

Lift capacity: Number of passengers the resort's lift system can move in an hour

Child friendly: Is the ski resort child friendly?

Snowparks: Does the resort have one or more snowparks?

Nightskiing: Does the resort offer skiing on illuminated slopes?

Summer skiing: Does the resort offer skiing during the summer?

The file snow contain data:

Month: Date to represent the month of the year (not just the first day)

Latitude: Latitude at the center of the region (every "region" is 0.25x0.25 degrees in size)

Longitude: Longitude at the center of the region (every "region" is 0.25x0.25 degrees in size)

Snow: Percent of time the region was covered in snow during the month

Alpine Skiing

## Overview

Alpine Skiing is a dataset for object detection tasks - it contains Ski annotations for 205 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This is a video dataset of a man skiing (mogul skiing). [Details] Category: Video / Subjects: Two Japanese male skiers in their 20s / Format: mp4 [Notes] [Shooting Time] 14 minutes 23 seconds
[Shooting Environment] Outdoors (ski resort)
[Shooting Distance/Angle] Simultaneous shooting from two angles

In the 2020/21 winter season, 36 percent of Liechtenstein's population participated in skiing, representing the highest share of any country in Western Europe. Meanwhile, around 35 percent of the Swiss population skied in the same year.

According to a survey conducted in November 2024, three percent of men and *** percent of women in Japan practiced skiing in the past year. Skiing was fashionable during the *****, as the Nagano Winter Olympics brought much euphoria (and investments) regarding winter sports in general and skiing in particular.

Skiing

## Overview

Skiing is a dataset for object detection tasks - it contains Person annotations for 206 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Map of Colorado Ski Resorts

Cross-country skiing audience profile for United States.

Demographic, psychographic, geographic and brand-affinity data for the Cross-country skiing audience in United States, sourced from Rascasse's panel of 12+ social and digital signals.

Discover the booming ski app market! This in-depth analysis reveals market size, growth trends, key players (like EpicMix, OnTheSnow, FATMAP), and regional insights for 2025-2033. Learn about the driving forces behind the industry's expansion and future prospects in AR/VR and wearable integration.

The data are related to two research articles: “The relative importance of ski resort-and weather-related characteristics when going alpine skiing” [1] and “Optimal pricing of alpine ski passes in the case of crowdedness and reduced skiing capacity” [2]. A rating-based conjoint survey experiment on active alpine skiers at a big ski area located in Inland Norway was performed in February of 2018 to collect the data and pertain to 400 respondents doing more than 7200 ratings. A total of ten versions of the same questionnaire type were used to obtain information about preferences on ski resort- and weather-related characteristics when going alpine skiing. We display the raw data organized such that they can be easily downloaded and used directly to either (1) replicate the analyses performed in the related research articles, or (2) run one’s own analyses on the topic of interest. The data may also be useful to lecturers teaching students about the key concepts of survey experiments and causal modelling.

Ski Resorts & Waffle Cabin Locations Dataset

This dataset provides a detailed view into ski resorts around the world, focusing on North America and including several resorts around the world. It has specifics on their features and geographic coordinates. Additionally, it encapsulates data on Waffle Cabin locations, highlighting their franchise status and association with specific resorts.

Dataset Details:

1. Ski Resorts:

   • Source: Data was responsibly scraped from onthesnow.com. (Disclaimer: Scraping was in compliance with the site's terms of use.)
   • Columns:
     • resort_name: Name of the ski resort.
     • state: State in which the resort resides.
     • summit: Peak elevation of the resort.
     • base: Base elevation.
     • vertical: Vertical drop.
     • lifts: Total ski lifts.
     • runs: Total ski runs.
     • acres: Resort's total acreage.
     • green_percent: Percentage of beginner (green) ski runs.
     • green_acres: Acreage dedicated to green runs.
     • blue_percent: Percentage of intermediate (blue) ski runs.
     • blue_acres: Acreage dedicated to blue runs.
     • black_percent: Percentage of advanced (black) ski runs.
     • black_acres: Acreage dedicated to black runs.
     • lat: Latitude.
     • lon: Longitude.

2. Waffle Cabin Locations:

   • Source: Data was sourced from the official Waffle Cabin website.
   • Columns:
     • Location: Waffle Cabin's location title.
     • Link: Web link to the location.
     • Is Franchise?: Denotes if the location is a franchise.
     • Resort Name: Name of the associated ski resort, if applicable.

Summary of skiing activity included in the study, showing distance, altitude drop, average and maximum speed, and duration of the activity for the two recreational skiers.

Ski Resort Market Outlook

According to our latest research, the global ski resort market size reached USD 21.8 billion in 2024, driven by a steady resurgence in travel and winter sports tourism. The market is projected to expand at a CAGR of 5.7% from 2025 to 2033, reaching approximately USD 36.1 billion by 2033. This robust growth is primarily fueled by increasing participation in winter sports, rising disposable incomes, and enhanced infrastructure development in both established and emerging ski destinations.

A key growth factor for the ski resort market is the rising global enthusiasm for winter sports activities, particularly among millennials and Gen Z. These younger demographics are not only more inclined to travel for adventure and experience-based holidays but also actively share their experiences on social media, amplifying the appeal of ski resorts worldwide. The proliferation of ski schools and beginner-friendly programs has further democratized access to skiing and snowboarding, making these activities attractive to a broader base of tourists. Additionally, the integration of advanced snowmaking technologies and year-round resort offerings has minimized the impact of unpredictable weather, ensuring consistent visitor flows and revenue streams throughout the year.

Another significant driver is the increasing investment in luxury and diversified service offerings at ski resorts. Modern resorts are evolving beyond traditional skiing and snowboarding to include high-end accommodations, gourmet dining, wellness centers, and a range of après-ski entertainment options. This diversification caters to the growing demand for holistic travel experiences, attracting not only avid skiers but also families, non-skiers, and corporate groups. The expansion of infrastructure, such as improved transportation links and digital booking platforms, has also enhanced accessibility and convenience, making ski resorts more appealing to international tourists.

Sustainability initiatives are playing an increasingly important role in shaping the ski resort market landscape. Resorts are adopting eco-friendly practices, such as energy-efficient snowmaking, waste reduction programs, and sustainable construction, to attract environmentally conscious travelers. These efforts are not only boosting brand reputation but also aligning with regulatory trends and community expectations. Furthermore, the ongoing digital transformation, including the adoption of contactless payment systems, online equipment rentals, and real-time weather updates, is enhancing the overall guest experience and operational efficiency, positioning the industry for sustained growth.

Regionally, Europe continues to dominate the ski resort market, accounting for the largest market share in 2024, followed by North America and Asia Pacific. The established infrastructure, rich skiing culture, and diverse resort offerings in the Alps and other European regions remain unmatched. However, North America is witnessing significant growth, particularly in the United States and Canada, due to increased domestic tourism and investments in resort modernization. Meanwhile, the Asia Pacific region is emerging as a lucrative market, driven by rising middle-class incomes and government initiatives to promote winter sports tourism, especially in China, Japan, and South Korea.

Type Analysis

The ski resort market by type is segmented into destination resorts, local resorts, and day resorts, each catering to distinct customer preferences and travel behaviors. Destination resorts are typically large-scale operations offering comprehensive amenities, including luxury accommodations, extensive ski terrain, and a variety of entertainment and wellness options. These resorts attract international and long-haul travelers seeking immersive, multi-day experiences. The demand for destination resorts has surged in recent years, driven by the growing trend of experiential travel and the preference for all-inclusive packages that cater to families,

This dataset contains input, output and reference data to the paper "Assessment of avalanche hazard of freeride skiing areas" submitted for publication in the journal Natural Hazards and Earth System Sciences. Authors: Adam Kupec, Štefan Koco (2025). Abstract: Freeride skiing and ski touring has been growing in popularity in Slovakia as an alternative to crowded ski slopes, offering skiers the thrill of untracked snow and challenging terrain. However, venturing into unmanaged mountain areas exposes participants to significantly greater dangers, especially avalanches and risk of falling. This study presents an approach for assessing avalanche hazard of freeride areas, demonstrated at the Jasná ski resort in Slovakia’s Low Tatras. Using high-quality elevation data, precise vegetation mapping, and historical avalanche records, potential avalanche release zones were identified, their potential run-out paths for skier trigger avalanches (≤ size 3) were modelled, and the frequency in which are avalanches likely to occur on different slopes were approximated. Results show that 15.9% of the area has high to very high release potential, with the most hazardous slopes concentrated on steep, north-facing terrain above 1700 metres. Simulations of more than 180 avalanche scenarios produced run-outs covering 44% of the area. Frequency analysis found that 64.9% of avalanche-prone slopes in freeride zones are subject to very frequent activity. Moreover, frequency approximation achieved 82,61% match with intersecting areas of the existing avalanche cadastre. Based on the results the freeride zones were divided into 4 groups based on their danger level. The proposed approach can be adapted to other mountain regions and may be further improved by automating vegetation mapping, modelling additional avalanche types, and using open-source simulation tools.

In 2024, ************************** was ranked as the best ski area in the world, achieving a ski index score of ***** out of 100. Meanwhile, *********************************************** ranked second, with a score of *****.