The Objectives
The goal of this assignment was to learn more advanced skills of model builder such as inline variable substitution and iteration. In the scenario for this assignment, the task at hand was to characterize ski runs from three different ski resorts by their skill level. The data provided included feature classes from Vail, Beaver Creek, and Breckenridge ski resorts, as well as slope, elevation, and aspect raster files.
The Process
First, an iterator was used to be able to run through the model multiple times to produce shape files for each of the feature classes. From there, a buffer of 10 meters was placed on each of the feature classes. Next, three "zonal statistics as tables" tools were used to join the three raster files given (aspect, slope, and elevation) which produced three tables. These tables were then joined (using the "join"tool) first with the original buffer output, then daisy-chained through the outputs that followed until all three of the zone statistics tables were used. This put everything into one table. Lastly, the "select" tool allowed a query to be used to create four feature classes, which included: beginner, intermediate, advanced, and expert classifications.
The Results
This model produced data that could be put into visual form in a cohesive manner. The data is easy to understand and gives the viewer a good idea of the layout of the slope. For example in the south central region of the resort there is a pattern of expert and advanced runs that one might perceive to be a ridge in the mountain.
Sources
All sources provided by Dr. Christina Hupy
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