Lab 8: Arc Collector - An Introduction to Gathering Geospatial Data on a Mobile Device, such as a Tablet or Smartphone

Arc Collector: An Introduction to Gathering Geospatial Data on a Mobile Device, such as a Tablet or Smartphone

Introduction

            This lab used the app Arc Collector to measure the micro climate of various points around the University of Wisconsin- Eau Claire campus. The purpose of the lab was to give students an introduction in the use of Arc Collector and the many types of research that it can be used for. In this project, students were separated into seven groups and each group took a various section of campus. The students then used a handheld micro climate device and compass to measure the wind speed, wind direction, temperature at the surface, temperature 2 meters above the ground, dew point, and type of surface. All of the information was collected using Arc Collector and then mapped used ArcMap.

Study Area

            The study area consisted of the University of Wisconsin- Eau Claire campus, located in Eau Claire, Wisconsin. The campus was split into seven zones. Two zones were located on upper campus, which contains most of the residence halls, the recreational center, and the dining hall. Two zones were located on the north side of the Chippewa River, where the fine arts building and the human sciences and services building are located. The other three zones were located on the main portion of lower campus (Figure 1). The zone that this group was assigned was zone 1, which is located north of the Chippewa River.

Figure 1. The zones of data collection on the University of Wisconsin- Eau Claire Campus.

Methodology

            A geodatabase containing a zone feature class and a microclimate feature class was already created for Joseph Hupy for this lab exercise. The needed domains and attributes were also created and assigned to specific fields within the microclimate feature class. Domains are created to make the data collection process more effective and more accurate. One domain was used to classify the types of surfaces possible, so the various students collecting data points could produce a uniform data set.

            Once, the microclimate survey was discussed in class, the Arc Collector app was downloaded. This app can be found in both apple and android app stores. The next step is to log on using the ArcGIS Online log in information. For this lab, the students needed to join the course ArcGIS Online group in order to get the survey onto Arc Collector. Once this is done, the project should show up in the Arc Collector app. The project  can then be selected and the app will show a map with the phones GPS location present (Figure 2). From this screen, one can select the plus bottom in the bottom left to start collecting a data point (Figure 3). The data points that are collected should appear in real time.

Figure 2. A screenshot for the Arc Collector app. This shows the already taken data points in red. The seven zones are outlined in red and the current location is a blue dot. 

Figure 3. This screenshot from the Arc Collector app shows what a new data point entry looked like for this lab. 

            The type of data collected in this lab was microclimate data throughout the University of Wisconsin- Eau Claire campus. The students were instructed to gather a relatively equally distributed data set for the assigned zone. At each sample located one student collect wind speed, wind direction, temperature at the surface, temperature at 2 meters above the surface, the surface type, dew point, and any other notes. The other student in the group then recorded this information in the Arc Collector app. Groups collected between 20 and 30 data points in the assigned zones. Once, data collection was completed, the students went back to the lab and used ArcGIS Online to download the data and open it in ArcMap.

Results

            ArcMap was used to analyze the data collected and the map patterns that emerged. The first few attributes that were analyzed were the various temperatures. Surface temperature varied throughout the study area (Figure 4). The most prominent pattern noticed in this map was the consist lower temperature on the walking bridge and near the river. The walking bridge has no earth beneath it to give warm, so this lower temperature makes logical sense. The south side of the river also has little tree protection, which could of helped in the lower temperatures as well. The main portion of lower campus varies a lot in the surface  temperature. The north side of the river has a lot of variability in surface type and therefore, is helpful in determine how surface type affects the temperature. It can be seen in Figure 4 that the grass or soil surface types, usually have a lower temperature than the black top surfaces. This makes sense, as it was a sunny day and the dark surface is efficient at absorbing the sun’s heat.

Figure 4. This map shows the surface temperature data taken throughout campus. 

            The next category that was analyzed was the temperature at 2 meters above the surface (Figure 5). The first thing to note is that the ground produced higher temperatures than the temperature at 2 meters, which is an expected result. Again, the temperature on the bridge above the river is lower than a majority of other places on campus. Overall, there appears to be less variability with the surface temperature at 2 meters than at the ground. This is again to be expected, because the temperature at 2 meters shouldn’t be affected by the surface type.

Figure 5. This map shows the temperature taken 2 meters above the surface. 

            Dew point was assessed next (Figure 6). The dew point varied from 15 to 43. At first glance, it appears variable throughout campus, but after a closer analyze a few patterns emerge. The bridge again, has a consistently lower dew point than other portions of campus. Upper Campus tends to have a lower dew point than Lower Campus. Lower Campus has a large range of dew points.

Figure 6. This map was used to display the dew point values taken throughout campus.

            The last attribute assessed is the wind direction (Figure 7). A rotational feature was used on ArcMap, so the arrows point in the direction the wind is coming from. On the river and north of the river the wind direction is most consistently west. A majority of Lower campus also has a westerly wind, but if the data sample is too close to a building there is some associated error present. On Upper Campus the wind pattern seems to more variant and possibly even have a north-east pattern. Many tall building may be the reason for this interesting wind pattern.

Figure 7. This map shows the wind direction present throughout the UWEC campus. 

Conclusion

            The microclimate data collected in this lab shows that the surface type affects the ground temperature. A paved surface caused the surface temperature to increased compared to a vegetated surface. It also shows that wind direction on campus has a lot of error due to the high amount of infrastructure present. Arc Collector was an effective and efficient way to collect this data. The most important aspect was the domains that were created before groups went out to collect data. This helped to keep the results in consistent units, even though multiple users were collecting the data.