Arc Collector Part One: Microclimate

Introduction
In this lab, Arc Collector was used to collect microclimate data on the UW-Eau Claire campus. Arc Collector has an app which allows one to enter attributes using the cell phone's GPS. This is very useful for collecting data quickly and efficiently out in the field, as well as allowing for multiple people to be inputing data at once.

Study Area
The chosen study area was UW-Eau Claire campus. The campus was split into seven zones, and groups of 2-3 students collected data from each zone. I was assigned to collect from Zone 2.
(Fig. 1 & 3). Data was collected around 16:00 on Wednesday, April 5th.

Figure 1. Map of 7 zones used to split up and collect microclimate data on UW-Eau Claire campus

Figure 3. A view of the zone map in
the ArcCollector app

Figure 2. The Kestrel 3000
weather meter

Methods
The attributes collected in the microclimate survey were temperature, dew point, wind chill, wind speed, and wind direction. A compass was used to measure cardinal wind direction, and all other attributes were collected using Kestrel 3000 weather meter (Fig. 2).

Figure 4. Data input function in
ArcCollector app

The zone map for the study area was provided by the UWEC Geography Department so data collection could begin as soon as the ArcCollector app was downloaded. To record a point, tap the plus symbol at the top, and then a screen pops up with a spot to record each attribute (Fig. 4). Once all groups collected at least 20 points in their zone, the maps were downloaded from ArcGIS online and opened in ArcMap desktop in order to create continuous surface maps. The interpolation method used in this lab was Natural Neighbors.

Results/Discussion

Figure 5. Map displaying the dew points at UW-Eau Claire campus. Measured in degrees Fahrenheit. 

 The dew points ranged from 30 to 58. The highest dew points were found in the parking lot behind the Davies center. The coolest places were in the corners and edges of campus.

Figure 6. Map showing the temperatures at UW-Eau Claire campus. Measured in degrees Fahrenheit.

 Temperatures ranged from 49 to 62 degrees. The warmest temperature areas were behind Phillips hall, right in front of Hubbard hall, and outside Towers hall. Coolest temperatures were recorded from north of the Chippewa river as well as Governor's parking lot.

Figure 7. Map showing the wind direction at UW-Eau Claire campus. Measured in degrees from North. 

 Wind direction ranged from 0.5 degrees to 340 degrees. Most of the wind directions were in the 120-150 range. The areas with higher wind directions were mostly found on lower campus and near the river.

Figure 8. Map of the wind chill variance at UW-Eau Claire campus. Measured in degrees Fahrenheit.

 Windchill measurements ranged from 45 to 62 degrees. Just outside of Haas was the coldest windchill, and Towers hall area had the highest windchill. As you can see, majority of campus had a windchill within the range of 50-53 degrees.

Figure 9. Map of wind speed at UW-Eau Claire campus. Measured in miles per hour.

Windspeed appeared to vary from 0 to 30 mph, however being in the range 15-30mph was rare. Wind speeds were greatest in the Oakridge parking lot on upper campus. Most of campus appears to have a windspeed of 0 to 4 mph. Upper campus also appears to have higher wind speeds than lower campus.

An anomaly that was noticed is the wind speeds in the range of 22-30 mph. On a day when the average wind speed was 1 mph, it does not make sense that there would be a microclimate wind speed that high. This could be due to human error or an error in the Kestrel device. Voids in the dataset include a time recording for each point (some were forgotten or not recorded correctly), and lack of elevation data. Elevation may have a significant impact on microclimate and it is important to take this into account when making inferences about the area.

Conclusions
 This lab demonstrated how to use ArcCollector to quickly enter data while out in the field and have it immediately be brought into a map. ArcCollector is very effective for surveying in groups and being able to gather a lot of data in a short amount of time. It allows for a wide range of functions and uses for the data and even automatically creates a web map (viewable here).