Four Applied Methods for Spatial Visualization in Snow Avalanche Forecasting

This thesis presents four applied methods for seasonal snow observation with respect to avalanches. Previous avalanche-related spatial variation and scale studies have shown a clear need for observation and methods to focus on the scale of interest to human triggering. These methods have the common goal to reveal spatial variation of interest to avalanche formation and human triggering in an efficient, accessible manner.;The four methods are: (1) A minimally destructive slope-scale sampling method, (2) A method to relate Google Earth terrain images to surface hoar formation in sparse trees, (3) A method of accessibly presenting complex GIS warming model data over real terrain, and (4) A method of measuring heat in the snowpack using a thermal imager. Despite their common goal of spatial visualization, each new method draws on a different subset of background literature and employs very different methods in development and use. Thus, each method is presented as a self-contained paper with independent results. Of note, these methods have all subsequently received active use, and conclusions from such use are discussed at the end of the thesis.