Field Exercise 7 - ArcPad Data Collection Part 2

INTRODUCTION

          In the previous blogpost (Field Exercise 6 - ArcPad Data Collection Part 1) I explained how to transfer a geodatabase from a desktop platform onto a portable GPS device. Unlike the previous exercise, where each group created their own specific geodatabase to be deployed, every group in this exercise will use an identical master geodatabase agreed upon by the class. In the previous blogpost I also explained how to collect and record climate data for the purpose of creating a microclimate map of our area of interest (AOI). In this field exercise seven groups of two will be measuring and recording climate within their individual AOI or zone. This climate data will then be stitched together to create one giant microclimate map which will encompass the entirety of The University of Wisconsin's Eau Claire campus. Finally seven different maps will be constructed to show off the individual climate data fields including wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity.

STUDY AREA

          The study area or area of interest for this field exercise is the entirety of UW-Eau Claire's campus as well as seven zones within the campus. The campus has been broken up into seven different zones so that each group of two can focus their measuring and recording efforts on a designated zone. In my partners and my case we were tasked with collecting forty climate points within zone seven. Below in figure one the seven different zones of the UW-Eau Claire campus can be viewed.

Figure 1: shows the seven different zones that the UW-Eau Claire campus was broken down into. The highlighted zone on the right hand side of the map (zone 7) was the zone my partner and I were tasked with measuring and recording climate data.

           Even though seven different groups are recording climate data in seven separate zones on seven different GPS units, this data will eventually be combined so that one comprehensive climate map can be created for the UW-Eau Claire campus. Breaking the campus down into individual zones and designating one zone to each group was a smart move because more data points could be measured and recorded within each zone; Otherwise, each group would have to cover too much ground and fewer data points would be recorded. This method of data collection also emphasizes collaboration between the individual groups. Only after communicating with each other and putting forth a group effort can the data recorded within each individual zone be added to the comprehensive campus climate map.

METHODS 

          The first task to be performed for this exercise was deploying the uniform geodatabase agreed upon by the class onto a portable GPS device. Again the device used was the Trimble Juno 3 handheld GPS unit and I explained the deployment process in the previous blogpost. The next step was measuring the 40 different microclimate points within our designated zone. Each microclimate point had to include the fields agreed upon for the master geodatabase which were as follows: wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity. These  seven different climate fields were measured using the Kestrel 3000 weather meter and recorded using the handheld Juno GPS unit. Figure two below shows the dispersal of the points my partner and I recorded within zone seven.

Figure 2: shows zone seven and the forty microclimate points. It can be seen that not all of the recorded points fall completely within the outlined area. The dispersal pattern of the points in general follows the walk ways of the UW-Eau Claire campus, however their are two distinctive points which appear on the roof of the building in the bottom of zone seven. 

          After my partner and I collected our forty points we had to transfer the recorded data from the Juno GPS unit into ArcMap. This process is also explained in the previous blogpost. Once our data was transferred my partner and I had to collaborate with our peers and create the comprehensive UW-Eau Claire campus microclimate map. In figure three below a comprehensive map of the UW-Eau Claire campus showing all the data points from the seven groups can be viewed. In table 1 below an attribute table of the merged data with the microclimate fields can be viewed.

Figure 3: shows the seven zones of the UW-Eau Claire campus as well as all of the data points recorded within. Each Individual group had to collaborate with each other in order to create this one comprehensive map.

Table 1: shows a snapshot of the data point merger of the seven individual groups. Points 142 - 169 are shown with their corresponding microclimate field attributes. From left to right the columns in the attribute data show wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity

          Now that all of the data points along with their corresponding microclimate attributes have been merged into one comprehensive map, the construction of seven different microclimate maps can take place. The seven subsequent maps were created using ArcMap, designed using Adobe Illustrator, and include a wind speed, dew point, surface temperature, temperature at two meters, wind chill, wind direction, and humidity map (figures 4, 5, 6, 7, 8, 9, 10 respectively).



Figure 4: shows a map of the wind speed on UW-Eau Claire's campus. I have used both a point feature class to show wind speed at the recorded data points and a continuous surface feature to show an interpolated average wind speed in between the recorded points. I also used the red boxes to delineate the seven zones. I used the Kriging method of interpolation to create this continuous surface.

Figure 5: shows a dew point map measured in Fahrenheit of the UW-Eau Claire campus. I have used a continuous surface feature to show the interpolated average dew point in between the recorded points. I also used the red boxes to delineate the seven zones. I used the Kriging method of interpolation to create the continuous surface.

Figure 6: shows a map of the surface temperature on UW-Eau Claire's campus. I have used both a point feature class to show the surface temperature at the recorded data points and a continuous surface feature to show an interpolated average surface temperature in between the recorded points. I used the Kriging method of interpolation to create this continuous surface.

Figure 7: shows a map of the surface temperature at two meters on UW-Eau Claire's campus. I have used both a point feature class to show the temperature at the recorded data points and a continuous surface feature to show an interpolated average temperature in between the recorded points. I used the Kriging method of interpolation to create this continuous surface.

Figure 8: shows a wind chill map measured in Fahrenheit of the UW-Eau Claire campus. I have used a continuous surface feature to show the interpolated average wind chill in between the recorded points. I used the Kriging method of interpolation to create this continuous surface.

Figure 9: shows a map of both wind speed and direction on UW-Eau Claire's campus. I have used both a point feature class to show wind direction in azimuth at the recorded data points and a continuous surface feature to show an interpolated average wind speed in between the recorded points. My partner and I were the only group to actually record wind direction, therefor, zone seven is the only zone shown on the map. I used the Kriging method of interpolation to create the continuous surface.

Figure 10: shows a percent humidity map of the UW-Eau Claire campus. I have used a continuous surface feature to show the interpolated average percent humidity in between the recorded points. I also added the red boxes to delineate the seven campus zones. I used the Kriging method of interpolation to create the continuous surface.



DISCUSSION

          The maps created above may look similar to one another, but there are subtle changes in each one to enhance the climate feature being displayed. Different color schemes, different symbology the addition or omission of the zone boxes, and different classification methods are but a few of the various ways in which the maps were tweaked. Creating the perfect map is always a tricky process and normally takes twice as long as I originally intended. This exercise was no exception. Finding the perfect transparency for the interpolated continuous surface was very tricky as well as simply fitting the map image into a aesthetic shape. I had a lot of difficulty cropping the first two maps until I realized that there was a ghost background keeping them from fitting onto a cropped background.
          As far as what the maps actually show regarding UW-Eau Claire's microclimate foot print, it's about as normal as it can possibly be. Two distinctive patterns that I did notice were that it is much windier on top of the hill than down in the river valley, and It is coldest right at the base of the hill where the cold air sinks and chills out. No pun intended.
          My partner and I encountered no problems with any part of our data set and I attribute some of this luck to the geodatabase domains established in the previous lab. Planning ahead of time by creating safety nets in the form of domains really helped our group once we were out measuring and recording microclimate data in the field.
          As discussed above, every individual group was held accountable for measuring climate data in their campus zone and merging it into the master geodatabase. Every group but one did not record the wind direction, ergo the wind direction map shows only zone seven. There was also a group that didn't measure the temperature at two meters. Although these oversights effected the group as a whole, they did not ruin the master data set.

CONCLUSION

          Overall this field exercise allowed me to go back over the process of transferring data to and from a handheld portable GPS unit, which was important because it can be a tricky process. This exercise also allowed me to brush up on my ArcMap and Adobe Illustrator map making skills. I spent roughly three and a half to four hours creating these microclimate maps and I could have spent double that If I really wanted to make them standout. This goes to show that aesthetics and creativity take a lot of effort and time especially with map making. After finishing this lab I feel extremely comfortable not only using a portable GPS unit but transferring data to and from it as well.