Lab 4: Pedestrian Networks @ University of Wisconsin Eau Claire
Goal:
The goal of this lab was to apply what we learned in the two network analysis workshops on ESRI's website. A network data set was created to process and understand a real-world network problem that someone could potentially face. The problem we worked on was the exploration of the Garfield Avenue construction project at the University of Wisconsin Eau Claire, which has been drastically affecting pedestrian traffic since the fall of 2017. More specifically, two routes were tested in this lab: the route pedestrians were forced to take in the fall of 2017 due to construction, and the new route that has been established currently in spring of 2018.
Additionally, a question was answered upon completion of the entire network analysis.
Question: What is the difference between the two routes in terms of distance and time? Were pedestrians losing time on their commute in the fall, and if so, how much time was lost?
Methods:
After completing the workshops on ESRI's website, a network dataset was created in Arcmap, which included the geodatabase providing the UWEC paths, barriers, and stops. Then, in the new network table window, UWEC paths were selected, and the option to turn on model turns was activated. In the 'evaluators' tab, the value of paths was changed to 'shape_length' to evaluate the distance covered in the path. Lastly, the travel mode was set to walking, well, because, we all walk in the provided path on campus. The data set could now be created so that the answer to the study question could be found.
An analysis was performed to determine the shortest path between point 1, the footbridge by Haas, and point 2, which is directly in front of Phillips Hall. To find this out, the routes were selected, loaded and then changed to the default value of 'Attr_length' from 0 to 1, and changing the field to 'Object ID'. Then, in route properties, the impedance was set to length in meters, which created a field in the attribute table that measured the distance of the shortest path after the analysis was ran. Finally, this process was repeated, but this time a barrier (near the footbridge) was loaded into the network, which allowed the distance of the longer path to be calculated.
Results:
For the route without the barrier, the total length was 429.9 meters (approximate) with a walking time of 5 minutes and 14 seconds.
For the route with the barrier (the longer route from fall 2017), the total length was approximately 517.4 meters with a estimated time of 6 minutes and 12 seconds. Both of these values could be found in the attribute table. Below is the map of the longer route.
The answer to the original question posed by Dr. Curtis can now be answered!
The goal of this lab was to apply what we learned in the two network analysis workshops on ESRI's website. A network data set was created to process and understand a real-world network problem that someone could potentially face. The problem we worked on was the exploration of the Garfield Avenue construction project at the University of Wisconsin Eau Claire, which has been drastically affecting pedestrian traffic since the fall of 2017. More specifically, two routes were tested in this lab: the route pedestrians were forced to take in the fall of 2017 due to construction, and the new route that has been established currently in spring of 2018.
Additionally, a question was answered upon completion of the entire network analysis.
Question: What is the difference between the two routes in terms of distance and time? Were pedestrians losing time on their commute in the fall, and if so, how much time was lost?
Methods:
After completing the workshops on ESRI's website, a network dataset was created in Arcmap, which included the geodatabase providing the UWEC paths, barriers, and stops. Then, in the new network table window, UWEC paths were selected, and the option to turn on model turns was activated. In the 'evaluators' tab, the value of paths was changed to 'shape_length' to evaluate the distance covered in the path. Lastly, the travel mode was set to walking, well, because, we all walk in the provided path on campus. The data set could now be created so that the answer to the study question could be found.
An analysis was performed to determine the shortest path between point 1, the footbridge by Haas, and point 2, which is directly in front of Phillips Hall. To find this out, the routes were selected, loaded and then changed to the default value of 'Attr_length' from 0 to 1, and changing the field to 'Object ID'. Then, in route properties, the impedance was set to length in meters, which created a field in the attribute table that measured the distance of the shortest path after the analysis was ran. Finally, this process was repeated, but this time a barrier (near the footbridge) was loaded into the network, which allowed the distance of the longer path to be calculated.
Results:
For the route without the barrier, the total length was 429.9 meters (approximate) with a walking time of 5 minutes and 14 seconds.
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| Figure 1: Route without Construction Barrier |
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| Figure 2: Route with Construction Barrier |
The difference in distance, between the two routes is approximately 267.5 meters and in time, the difference was about 1 minute. This difference, especially the difference in time seems suspect, but if you add that up over the course of a semester, it turned out to be quite the difference! If you walked to and from campus every day on this route, you would've walked an extra 150 minutes, or 2.5 hours! If you happened to walk this route more than once (like me), the extra time could've been anywhere from 200 extra minutes, to up to 500 extra minutes! Wow, that could calculate to another 10,000, or almost 3 pounds of fat all because of construction.
Sources
Sources
Curtis, C. (n.d.). [UWEC_paths, UWEC_stops, and UWEC_barrier feature classes]. Accessed on March 7, 2018
ESRI. (2018). World Topographic Map. Accessed on March 7, 2018. https://www.arcgis.com/home/item.html?id=30e5fe3149c34df1ba922e6f5bbf808f
University of Wisconsin- Eau Claire. (n.d.). Garfield Avenue Redesign. Accessed on March 7, 2018. https://www.uwec.edu/facprojects/garfield.htm
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