Exercise 2

Goals

The goal of this exercise was to dive deeper into model builder and get more experience with its many uses. In particular, the use of model iterator and inline variable substitution. In this exercise, the given scenario is that we have obtained line feature classes for existing ski runs on resorts in Colorado. We want to understand the topographical characteristics of the runs. We also want to execute tools on the feature classes multiple times.

Methods

To start of the exercise, data had to be acquired from the class folder. As stated earlier, the data were multiple feature classes showing the ski runs of multiple ski resorts. Once the data were gathered, the model could be built. The first objective in the model was to add the iterate feature classes tool to the model and connect the input workspace. Once the iterate feature classes tool was in the model and the parameters were set, the buffer tool was added to the iterate tool. This made it so that every feature class that was sent through the iterate tool would be getting a buffer. Once the buffer tool was in place, the zonal statistics tool was added. The zonal statistics tool was used to gather data from the rasters that were provided in the geodatabase. These rasters would provide statistics to each of the now buffered ski run feature classes. The next task was to use the join field tool. This was used so that it would join the zonal statistic output tables to the buffered feature class. The final task of the exercise was to use the select tool and an SQL statement to create four new feature classes. These feature classes would rank different sections of the ski runs from beginner, intermediate, advanced, and expert. 

Results

The results of the model shown below as Figure 1, have been placed into a map that is labeled Figure 2. The map shows each of the three different ski resorts and their ski runs. The sections of the runs that were categorized by the final select tool, were classified as follows:

Blue - Beginner

Green - Intermediate

Orange - Advanced

Red - Expert

Figure 1 shows the model that was built to execute the desired tools.

Figure 2 shows the maps that were produced from the above model.

Conclusion

Exercise two did a good job of building off of exercise one. We dove into some more advanced model builder tools and got some experience with iterator and inline variable substitution. Both exercise one and two have done a good job of getting us more comfortable with the different tools that can be used in model builder. As for the data that was processed in this exercise, I thought it was fascinating how the maps turned out and showed the different levels of ski runs.