Collecting Data Using Arc Collector

Introduction:

In 2014, the undergraduate population of UW-Eau Claire (UWEC) was recorded to be just over 10,000 students with 62% said to be living off campus (http://colleges.usnews.rankingsandreviews.com/best-colleges/uw-eau-claire-3917/student-life). This means that available student parking is often in high demand. Although ample amount of parking lots can be seen around campus, monthly permits are required with starting fees ranging from $100-$200 (depending on the month purchased) and an additional $5 dollars a month to renew it. As a result, street side parking often becomes a preferred method. However this data leads to the question of if alternative parking, in the form of parking meters, was more wide spread, would it be utilized? Even though this question is more in depth than this study requires, it does lead to a more generalized set of questions. Such as; Where are UW-Eau Claire's parking meters located? How many parking spaces do they entail? Are parking meters spread out or clustered? If they are clustered, where? And, are these spaces being utilized?

Study Area:

Figure 8.1 is a map depicting UWEC's campus, which is the area of interest for this study.
Figure 8.1: UWEC campus with respective zones of study.
As can be seen on the map, the campus was separated into three zones; upper campus, lower campus, and "Water Street" campus". By doing so, attributing parking meter data could be better analyzed once data was collected.

Methods:

To start the process of data collection, the first step was to create a personal geodatabase that contained self-determined feature class, attributes and domains. To answer, the above stated questions, fields such as: time allotted, number of days enforced, number of parking spaces per meter, number of spaces occupied, and zone in which the meter was located, were all created. Then domains were specified to create parameters. These included the total number of days enforced (short integer, ranging 1-7), the number of parking spaces per meter (float, 1-4), maximum time allotted for parking (coded values; 20 minutes, 2 hours, other), and zones on campus (coded values; upper, lower, and Water Street).

Once this was all established, the geodatabase was shared as a service to the public through ArcGIS Online. This service could then be found under the creators "MyContent" tab on ArcGIS Online. From here, the service layer was added onto the mapping feature on the creator's account and then shared to the public again.

From here, data and attribute collection could begin. To do so, Arc Collector (an application which was previously downloaded onto a personal mobile device) was used. Once all point and attributing data was collected out on the field, the layer was added back onto ArcMap to be futher edited and analyzed.

Results and Discussion:

On April 1, 2016 from 11 AM to 1 PM field data on parking meters was collected on the UWEC campus. From this, a total of 84 meters were recorded with a resulting 206 associated parking spaces. Of these 84 meters, 6 were associated with only one parking space, 58 were connected to 2 parking spaces and the remaining 21 meters were linked with 4 parking spaces.

Figure 8.2 depicts the total number of meters and their respective times that were allotted. Some trends that appeared from this data was that in general, the parking meters were in fact clustered. With 7 out of the 12 building that were recorded to have parking meters outside of them being student housing. However, this only accounted for 95 of the 205 parking spaces available, with the left over 111 spaces clumped in the parking lots affiliated with campus facilities (i.e. classes, fitness center, conference rooms, and dining) Another trend to be noted was that all the times that were associated with the time frame of "other" (red in color, and were 3 hour limits) were all located outside these campus facility buildings.
Figure 8.2

Figure 8.3 is a split image map that looks at the number of total parking meters, the total days enforced, and the number of available parking spaces verses the number of occupied spaces on upper campus. Some patterns to note is that all of the parking meters on upper campus were enforced 7 days a week, and that only the parking meters located in front of Crest Wellness Center and Governor's Hall had four space parking meters (top half of figure 1.3). While analyzing the second, bottom half of figure 8.3, it can also be noted that the number of occupied spaces (11 total) never surpassed one, no matter the number of parking spots available.
Figure 8.3

Figure 8.4 looks at the same aspects as the last figure, however for lower campus. On the top portion of this map, it can be see that the number of parking spaces available is much more stratified per parking meter, and aside from the parking meters outside of Davies Center, all of the meters are still enforced 7 days a week. When looking at the bottom portion of this map a few other observations can be made. First is that that parking meters outside of Schneider Hall had a high level of occupied stalls, and secondly that that total number of occupied stalls (23) is much higher than upper campus. This however is probably due to the time of day and week. Lower campus has a much larger number of facility building over student housing and thus more car traffic would be expected on lower campus over upper during that time.
Figure 8.4

The final figure, 8.5 depicts the same aspects as the last two figures just for "Water Street" campus. The first thing that can be observe is that each meter observed is enforced only 5 days a week and that the time allotted for each meter was 3 hours. It can also be seen that of the 22 meters available, which equals 60 spaces, 15 were occupied. Again this is probably be directly attributed to the time of day and week.
Figure 8.5

Conclusion:

In conclusion to the generalized questions for this study, the parking meters on UWEC campus can be found outside of campus buildings in all zones indicated. Although there was a slightly higher number of parking meters on upper campus, the number of spaces available was lower than what can be found within lower campus. This then directly correlates with the higher number of parking spaces occupied that were found on lower campus. In future studies of this topic, a longer time frame and over week days and weekends at different times during the day should be looked at. Once this data would be analyzed, a better understanding of the whether more parking meters in specific locations on campus can be utilized.

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