These five networks show patterns of movement and preferences within the ski community related to physical location as well as communal aspects like ski brand loyalty.
1. MOVEMENT- Skiers move to and live in regions that support snow-based lifestyles. Often there are patterns that occur out of the movement of skiers. For instance, those who grew up on the East Coast show more movement out West over those who grew up in the West moving East. Other patterns show seasonal movement, such as people moving to glacial areas or the Southern Hemisphere during North American summertime. Looking outside the US you see a similar patterns in Canada where the West Coast seems to draw large crowds. The movement network will track skiers around the globe plotted on an XY chart showing patterns of "migration" in movement.
2. SNOW FALL - Amount of snowfall draw skiers to different regions of the world. Places such as Niseko, Japan are known for their incredible quality and quantity of snow and become targets for skiers all over the globe to move to. Although city snowfall doesn't always represent the snowfall in surrounding ski areas such as Denver compared to resorts located nearby in the Rocky Mountains. I would like to explore this network of average snow fall around the globe by utilizing maps portraying snow depth. To help show what areas get the most snow my visualization will have snowflakes falling that correlate to particular cities in the world and their size will represent average snowfall.
3. ELEVATION - Like snow fall, elevation plays an important part in the surrounding atmosphere of a city or town. Higher elevation areas generally receive more snowfall and therefore draw in larger crowds from around the world. Although not one of these networks is the defining aspect of where skiers move to they all play a big role in attracting people. By looking at the popularity of cities by elevation we will be able to see whether there is a true correlation. In my visualization this network will show the elevation of ski related cities plotted on a chart that creates a mountainous appearance.
4. SKI BRANDS - Different ski brands find niches in different regions of the globe. With more and more people focused around sustainability ski companies are starting to introduce new products that cater to this conscious effort. The sustainability factor is also supported by the locals when it comes to community support. When riding on the mountain there is always a network of who owns which skis or which new gear. And this network of ski brands connects people around the globe because they become attached to a particular company. Skiers who support certain companies over others show a loyalty and help to build that company's network in whatever region of the globe the skier is located. The network visualization will utilize ski brand logos to depict the regions they are found or are most popular in.
5. SKI RESORTS - Skiers tend to move to cities and towns within range of ski resorts and backcountry riding. Some cities give access to skiers both backcountry and resort skiing such as Salt Lake City, Utah while others cities require hours of driving just to ski a couple hundred vertical feet. Either way, people are drawn to skiing and they will make do with whatever they have. One reason for such vast migration of East Coast skiers to the West is the larger mountains that have larger ski resorts as well as more terrain for backcountry riding. Using data from skier movement I hope to show with this network the most popular ski resorts according where people live.
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