| Avalanche forecasters are faced with ever-increasing pressure to make more informed decisions and accurate predictions. Decisions often need to be made very quickly and face criticism from many different parties. Therefore, forecasters need a means to be able to synthesize data efficiently and effectively. The development of a better support system for decision makers and avalanche forecasters by incorporating new methodology into time-honored and proven methods is the goal of this research.; With the vast amount of data being produced, visualization is an improved and effective method for organizing, analyzing, and communicating complex data. This finding is supported by studies showing that the human mind assimilates complex information better when displayed graphically versus text-based or numerical representations. In order for visualization to be effective, it needs to be presented in a manner that is consistent with the cognitive, perceptual, and response-based mental representations of the user.; This research develops a new method to visualize multiple spatial data sets that are factors in determining snow pack stability in an intelligible holistic form that maintains the contribution of each data set. The spatial visualization model synthesizes multiple qualitative and quantitative spatial data sets into a single, clear, more comprehensible representation without losing important information. The visualization method allows the user to be able to drill down deeper or drill up to analyze individual data sets. In addition, a range comparison technique is developed to allow a set of chosen parameters to be compared with historic data in order to determine similar historic analogs. The result is an intuitive software program that allows users to analyze multiple complex data sets through a graphical user interface. The potential benefit of the visualization model is assessed through a user evaluation conducted along the Wasatch Front in the state of Utah. |
