Introduction
Easier methods to data collection are up and coming every day in the geospatial world. With the evolvement of the geodatabase, data collection in the field has become easier. The use of handheld GPS units allows researchers to get exact point locations, but also collect data into the geodatabase. With setting up domain ranges, it prevents error in data entry and/or allows you to use coded entries that includes a list of options. The geodatabase also gives the list of data entries needed like ground cover and wind speed. By inputting the values into the GPS, it saves time compared to manual imputation into a spreadsheet or program and directly transfers the data to the feature classes specified.
Study Area
The study area for this exercise consisted of the University of Wisconsin- Eau Claire campus. We were to pick an area of our choosing, but try to get diversity in our environments and not stay within one area. Specifically, my group chose to survey the lower campus the included the surroundings of the academic buildings, campus green space, and the river corridor (Fig 1). The weather observations were cloudy, cool (low 20's), and breezy.
Figure 1. Map of UWEC Lower Campus.
Methods
If recalled in Exercise #5, we were to develop a geodatabase to collect micro-climate data. This week we were to pick up from that exercise and prepare and deploy the geodatabase for collection with ArcPad. To begin, we were to use ArcMap to prepare a map project to deploy and check the data back into. In this project, the first step was to open the feature class that was created last week with the micro-climate fields. The next step was to then add a basemap for a visual while collecting. This was to be our choosing, and our group chose to use the Eau Claire County Ortho Map that was available in the Q:\\ Drive on the school database.
The next step was to deploy the geodatabase to ArcPad to collect data. To do so, the ArcPad Data Package must be activated in the Extensions in the options of ArcMap. Once activated, the ArcPad toolbar can be viewed and used (Fig 2). On the toolbar, the deploy button can be hit, and the tutorial window will pop up (Fig 3). The next button can be hit on the introduction. Next you must hit the "deploy all data and layers" (Fig 4; Fig 5). Next, you will want to establish a file name and choose the location where the file will be saved (Fig 6). Make sure the Create file on this computer box is checked, and the finish button can be hit (Fig 7). ArcMap will then prepare the file for use on the ArcPad program.
Figure 2. Location to access the ArcPad Toolbar in ArcMap.
Figure 3. ArcPad Toolbar in ArcMap. The button labeled 1a is used to deploy the geodatabase for data collect. Button 1b is used to check in data after data collection.
Figure 4. Deployment tutorial showing how to check out all layers for deployment. To access the menu, the user must right click onto the "Action" bar.
Figure 5. Tutorial screen showing that all layers have been checked out and the user is ready to move on in the tutorial.
Figure 6. The third screen of the deployment tutorial. User will want to make sure that the spatial extent is set to the current display extent, choose a file name, choose the location to save the file, and to create a ArcPad map (amp) file and name it.
Figure 7. Last screen of the deployment tutorial. User will want to create the ArcPad data on the computer now and Finish the tutorial for processing.
Within your files, you will now find a file that you named during set-up. Copy and Paste this file into the same folder to have an extra copy of contents incase something goes wrong with the original.
To collect data, a Trimble Juno 3B handheld GPS unit will be used. This unit contained the ArcPad software (Fig 8). To load the files onto the GPS, we plugged the GPS units into the computer and copied the deployment file to the SD card in the GPS. The geodatabase is now ready to collect data.
Figure 8. Example of the handheld Trimble Juno 3B GPS unit used for data collection.
To collect data, a Kestrel handheld weather station was used (Fig 9). This unit was able to tell the wind speed, wind chill, temperature, humidity, and dew point. The only information it could not tell was the wind direction. Along with these variables, the surface type and any notes were also recorded. By using the geodatabase, data collection was easy. By hitting a new data point on ArcPad, it recorded the GPS location and gave input fields for each of the variables. The wind speed, wind chill. temperature, humidity, and dew point were all manual inputs that numbers must be entered. The ground type was a coded domain, so choices were given in a drop down option. The notes category was also a manual typing method.
Figure 9. Example of the Kestrel handheld weather station used for data collection.
Temperature was recorded at both the surface (ground level) and 2 meters up from the ground in degrees Fahrenheit. The wind speed was recorded by placing the unit in the air above the human body in miles per hour. Dew point and humidity were recorded in whole values.
When all data collection was complete, the GPS was then pulled back into the computer. By copying the files off of the SD card and pasting into our personal folders, ArcMap then can check in the data using the check in button on the ArcPad toolbar (Fig 10). The data points should now show up onto the basemap and the attribute table should be full.
Figure 10. Tutorial screen for Checking-In data after collection. The green button in the upper right hand corner allows user to navigate to the folder holding the data. Once data is located, the feature class(es) that need to be checked in can be selected and "Check In" can be hit to finish the process.
After the data has been checked in, raster interpolation methods can be used to form a continuous surface map. In this case, IDW was used to form multiple maps of different microclimate attributes.
Results of Microclimate Survey
Figure 11. Map of Dew Point on the UWEC Lower Campus. All readings are in degrees Fahrenheit.
Figure 12. Map of Temperature on the UWEC Lower Campus. Temperature readings were taken at the ground level. All readings are in degrees Fahrenheit.
Figure 13. Map of Humidity on the UWEC Campus. Readings are in percent humidity.
Figure 14. Map of Temperature on the UWEC Lower Campus. Temperature readings were taken at the 2 meter mark above ground. All readings are in degrees Fahrenheit.
Figure 15. Map of Wind Speed on the UWEC Lower Campus. Readings are in Miles per Hour (mph).
Overall, the microclimate of the Lower UWEC campus seemed to vary a lot. Higher dew points were found along the river corridor (Fig 11). Temperature at the ground height was found cooler along the river corridor when compared to in-land campus (Fig 12). This was also found for the temperature at the 2m height above ground (Fig 14). The humidity rose as one got closer to the river (Fig 13). The wind speed varied greatly over the lower campus and no distinct pattern was seen (Fig 15).
Discussion
This was a great exercise to learn about ArcPad, the steps to deploy and check in a geodatabase, and some of the implications that can occur. Although we looked at weather, it the was the ideas behind the exercise that were the most valuable.
Although programs like ArcPad make data collection easier, there are many implications that can occur. One issue observed was getting the data to deploy in ArcMap. UWEC has their own campus basemap that could be used to simply show the buildings, parking lots, and other land features. Although it is a basemap, we were not able to get it to deploy for the GPS. After trouble shooting, it was decided it was much easier to use a DEM map that was already on file.
After deployment some data collection errors also occurred. Without a compass, wind direction was not able to be measured. Some other implications I also observed was the way the Kestrel unit needed to be held to record certain variables. It needed to be held higher for wind speed and wind chill, while different temperatures could have been observed it not enough time was given for the unit to adjust.
Although these maps show varied results for the lower campus, only 20 data points were collected. This is a very small amount of data points and to see true differences then more should be collected.
Conclusion
This was a great way to look at what a geodatabase can do besides store data. With techniques like this one, it can simplify the collection and imputation process tremendously. It was also interesting to see how weather patterns can change over a short distance (like a college campus) depending on different ground covers and proximity to bodies of water. Geospatial technology is truly amazing with the applications one can utilize. Although it seems ArcPad is becoming a little outdated, it was still a excellent introduction to mobile data collection.
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