In this lab a Kestrel unit was used (Figure 1). This tool measures wind speed, temperature, dew point and a few other things regarding weather. In this lab, the class was split into eight different groups. These groups went to different areas around campus marked out by a map (Figure 2). I was assigned to zone one. This included the footbridge and the area on the Water St. side of campus. There were five different zones that groups were to take data points and measure wind speed, wind direction, temperature, and dew point. The data points were collected and the attributes were typed in using arc collector. This software allowed the class to all record their data points at the same time. As groups were looking at their maps, other points from other groups were popping up all over the place. This was very interesting to see where other groups were taking points.
Figure 1: This is the Kestrel unit that was used to collect the attribute data (temperature, dewpoint, and wind speed) at each point.
Figure 2: This map shows the different zones in which data was collected. Zone four had no group so there is no data for zone four.
Methods
At each point on our phones we were able to hit a button that said mark point. This then allowed the students to type in the attributes at each point. The attributes were wind speed, wind direction, temperature, dew point, and there was a place to put notes. Group one even attached an image to one of the points collected. This data was collected using arc collector in ArcGIS online. This made the data very easy to export into ArcMap allowing us to create specific maps based on these attributes.
Results
This exercise was great for making the students work together in coming up with a process in gathering the data. There were no real patterns besides the fact that when we were close to the river the wind always came from in the river valley. There were times at points we collected that there was no wind. Another thing we noticed was that when we were closer to the water the temperature was higher than it was around other parts of zone one (Figure 3). This surprised me. I assumed that the temperature would have been cooler around the water. The dewpoint data that was collected was very similar to the data that was collected for temperature (Figure 4). The same trends that were seen with temperature were seen with dew point. The wind speed shows that many of the points the wind was almost non existent (Figure 5). This tells us that the wind was not really blowing and many of the students had no data to collect in places.
I chose not to include my wind direction map as after discussing with groups it sounded as though we had different methods of collecting this data.
Figure 3: This map shows the different temperatures that groups collected around campus. As you can see in zone one the closer the point is to the river the higher the temperature.
Figure 4: This map shows the data for dewpoints around campus. This map correlates to figure 3 showing the temperature.
Figure 5: This map shows the wind speeds of the points collected around campus. There were many of these points that had no wind data to collect.
After these points were transferred into ArcMap the attribute data was tied to each point (Figure 6). This data was included when the points were collected. The attributes included temperature, wind speed, wind direction, dew point, and extra notes.
Figure 6: This image shows the data that was collected for each point. This is the attributes for one specific point gathered by group one.
Conclusion
This lab did a great job in showing students that there are easy ways to collect data. This data is then easy to put into ArcMap to be worked on. This makes life much simpler for people to do what they want with the data.
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