Exercise 9: ArcCollector

Introduction:

The question posed for this study was "how many coffee shops are located in each of the defined neighborhoods for Eau Claire?" This question will provide data of how many coffee shops are located in neighborhoods that are in student population for UWEC. It will also show the proximity of coffee shops that are close to campus for alternative places to study and also provide the resource fro readily available caffeinated drinks.

Study Area:

The study area for this study is in the City of Eau Claire. Neighborhoods were defined using Realty definitions and defined areas from the City of Eau Claire. Coffee Shops were only mapped within the city limits, since this is where UW-Eau Claire is also located. The center of the study was defined as 105 Garfield Ave. This location is in the heart of campus and is specifically the address to the library.

Methods:

The data needed to be prepared in ArcGIS Desktop before being able to use the web app of ArcCollector. First a geodatabase needed to be started. In this case, it was called EauClaire_Coffee_Shops. The domains for the geodatabase needed to be established. Domains are rules that describe the values of a field type, enforcing data integrity. Domains included Food, Neighborhoods, Coffee, Type. Coded values were added to those that could be answered without having significant or diverse values. Table 1 shows the attribute table with the data filled in after the data collection was complete. 

Table 1. The attribute table of the Coffee_Shop_Locations after the data was collected.

After the domains and fields were established with its proper type, the geodatabase needed to be published. Using ArcGIS online, a new map was created. The street basemap was selected and the layer was added to the map. Once the map was saved, it could be used in ArcCollector.

The data was collected by driving around the study area and taking points at the front door of every coffee shop. The attributes were filed out for each feature class. Figure 1 is an example of what ArcCollector looks like on a phone.

Figure 1. Screenshot of ArcCollector on a phone.

After the points were all collected, the map could be downloaded so it could be manipulated in ArcMap.

Results/Discussion:
Figures 2 and 3 show the location of the coffee shops around Eau Claire. Each shop was within a 6 mile radius of the central point at 105 Garfield Ave.

Figure 2. Locations of the coffee shops around the study area of the City of Eau Claire.

Figure 3 looks specifically at where the coffee shops are located in respect to the neighborhoods. Typically UWEC students live in Randall Park as well as the Third Ward. Part of Downtown Eau Claire also lies within the Third Ward. Three of the 18 coffee shops are in Randall Park and four are located in the Third Ward. These two neighborhoods have the most coffee shops within them. The market for students is more likely to be reached in these areas anyway.

Figure 3. Locations of the coffee shops within the defined neighborhoods.

Other factors that students could make when deciding on which coffee shop to stop at were mapped. The first one being the distance coffee shops are from campus. Figure 4 consists of a 3 ring buffer at 1 mile each. Many students do not have a car, so the shops that are closer in proximity are going to be greater target. Two of the coffee shops are located on campus, but their hours vary and they are typically not open on the weeks.

Figure 4. Distance of coffee shops from campus.

Another factor that some consider is the type of coffee sold (Figure 5). Some people are interested in where their coffee is coming from. Six of the coffee shops provide Fair Trade coffee, specifically Caribou Coffee. For those that are looking to be environmentally friendly as well, one shop (ECDC) sells organic carbon negative coffee.

Figure 5. Coffee shops defined by the types of coffee they buy.

The last factor that was considered was deciphering is a coffee shop was part of a chain or local (Figure 6). Seven of the 18 shops are part of of a chain (Starbucks, Caribou), leaving the remaining 11 as local assets to Eau Claire (Racy's, Acoustic).

Figure 6. Defining if the coffee shop is local or a chain.

Conclusions
The proper project design is essential when collecting data in the field. Feature classes, domains, and fields need to be established before data collection. Once you are in the field, there is so way to go back and change or add things. One thing that I forgot to add was a notes section. This is an essential field when data collecting. Significant feature can be noted or new feature ideas that could be added later can be typed up in the notes. After driving around the entirety of the City of Eau Claire, an analysis on the types of areas that these shops were located could be used for future expansion. This project could be taken to the extent of trying to do site selection based on drive/walk times, customers, competition, and markets.