This is a "Data science for social good" project started during the course of Applied data analysis taught by Prof. West at EPFL. It received the Best projects award (5 out of 100) and was presented during the Applied Machine Learning days '18 in Lausanne. You can check out the website and our poster.
Risk zero does not exist in alpinism. Statistical models have been developed to assess this risk but they do not prevent tragedies. We do not claim that we can do better, but given that most of the accidents are due to bad people decisions, we are convinced that raising concern about the past mountaineering accidents can strongly improve alpinists' judgement in the future. The aim of this project is to gather meteorological and environmental data (weather condition, precipitations, snowpack, wind, temperatures, slopes, exposures, time of day…) along with avalanche cases and casualties. By leveraging means of interactive visualization, we will provide the skiers ways to understand the conditions of previous cases and maybe hints that could have changed the outcome. Our observational study will focus on the Swiss Alps.
We scrapped data from the SLF archive and applied some image processing on the maps. You can contact us if you want the raw data (in an S3 bucket).
- Jean-Baptiste Cordonnier @jbcdnr
- Brune Bastide @brunebastide
- Arnaud Lesimple @arnaudlesimple