Snow Stats: Using Big Data to Help Ski Areas Survive Global Climate Change
C.J. Sullivan, The Data Incubator
I have a passion for skiing. But I am growing increasingly concerned about the dwindling levels of snowfall at our country’s ski resorts, where global climate change is making an alarming impact. Ski resorts, in order to remain profitable under such variable snowpack conditions, must adjust to this volatility by using analytics to “predict the weather” well in advance of the upcoming season. This analysis, coupled with data-driven decision-making, can make the difference between a profitable ski resort and one that will go out of business.
In this talk, we will discuss how to predict snowfall by correlating historical satellite imagery with known weather conditions. This imagery is obtained from the LANDSAT satellites, which have imaged the entire planet at 30 meter resolution dating back to 1970 at a variety of spectral bands. We will discuss the creation of algorithms to potentially analyze petabytes of imagery and what type of information could be obtained from that analysis. We will discuss the tools and techniques necessary to analyze large weather-related datasets, as well as how global climate change (and our response to it) will impact the future of skiing. Join us!
About the speaker
Clair J. Sullivan is an Assistant Professor in the Department of Nuclear, Plasma and Radiological Engineering, at the University of Illinois at Urbana-Champaign (UIUC). Professor Sullivan recently received the DARPA Young Faculty Award to focus on Big Data and is currently enrolled at the Washington campus of the Data Incubator, a data science training program. In her spare time, Professor Sullivan enjoys spending time with her family, traveling, and of course, skiing!