Date of Award

6-14-2023

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2023.

Department

Computer Science and Engineering

First Advisor

Sean Choi

Abstract

Our Avalanche Prediction Model utilizes machine learning to analyze weather and climate data in order to provide users in the Northern California back-country with accurate probabilities of avalanche occurrences. Snow forecasts only provide information relating to how much snow will fall. Current avalanche danger ratings only provide the potential level for injury there is if an avalanche will occur. Our system, Avy Safe ML, let’s users survey geographic terrain and see direct probability indicators for precise geo-locations of mountain faces and ranges. These indicators are represented as variably-shaded geo-polygons that indicate avalanche risk classifications. Our data visualization allows access to the results of calculations accomplished by our support vector machine model all in a user-friendly experience. Avy Safe ML hopes to provide back-country folks with the ability ”know before they go” into potentially dangerous terrain.

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