Author: Simon Horton

An R package for snow profile analysis and visualization

R has become one of the dominate programming languages for statistical computing. This poster provides an overview of the recently published sarp.snowprofile package, which includes functions for importing/exporting, formatting, plotting and manipulating snow profile data in preparation for statistical analyses.

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A new set of perceptually effective colour palettes for snow profiles

Visual representations of observed and simulated snow profiles aim to convey critical snowpack information in a quick and easy-to-understand format. While colours are an important component of visualizations, they have not received much attention in our community. We present a new set of colour palettes for grain types designed with visual perception and information visualization principles. The palettes emphasize important snowpack features relevant for avalanche forecasting.

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How close are we to automated avalanche forecasting? Lessons from testing machine learning methods in Norway and Canada

Artificial intelligence methods are increasingly applied in many areas in our daily lives and have fundamentally changed how decisions or services that require analyses of complex data are provided. Could this be the holy grail for avalanche forecasting as well? In this poster, researchers from Simon Fraser University and the Norwegian Water Resources and Energy Directorate share lessons from their explorations in machine learning and discuss their plans for future research and development.

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