Field Activity #8: Microclimate

Introduction:

This activity directly corresponds with the previous one which was setting up the geodatabase that would be used to take microclimate data. In the previous lab we pre-planned our actions for the microclimate collection. There were several factors that we all had to create for the purpose of normalized collection. The list below shows the areas of recorded values. Groups of two were then deployed for the collection of the values. My partner was Carolyn McLeish and our region of campus was around the lower campus residence halls. This can be seen in image 1 below. Other groups took data on upper campus and around the river. The goal of the data collection is to identify microclimates on our campus. Through the analysis of these microclimates it appears that climates can be very different over very small distances.

Recorded Values:
-Time
-Group
-Temperature
-Dew Point
-Relative Humidity
-Wind speed & direction
-Snow Depth
-Other groups had additional

Image 1: The above image shows the points that were collected in the field using the Juno 3D device. The Juno allows the user to use ArcPad to update  tables into points on a map syncing it with GPS coordinates.

Methods:

Several methods were used for collecting the microclimate data. The entire process was completed by walking through a specific section of the campus and taking readings. A ruler was used to measure snow depth while a Kestrel meter was used to find all of the other values. All of the values that were collected appear above under the recorded values section.

Deployment of Data:

In order to deploy the data into the Juno 3D device, the ArcPad Data Manager extension must be turned on. This allows for the adding and editing of data from the Juno to the ArcMap software. The Juno device must be plugged into the desktop in order to complete the next portion of the activity. The geodatabase that contains all of the data must be opened in order to to transfer it and its feature classes to the device. The ArcPad Data Manager then runs the user through the Wizard process which essentially creates the storage within the device. Once the wizard is finished the deployment folder will be created. We made a copy of that folder to ensure integrity if the data gets messed up in the field.

Image 2: The picture here shows the Juno 3D device. It is created by Trimble, who makes many of the most advanced handheld GPS units. The one that we used was very user friendly and had a touch screen.

Collection of Data:

To begin collecting data the Juno devices ArcPad software must be activated. Once ArcPad is running add the image and geodatabase that was uploaded to the device. Once these are added editing can ensue by adding points to the map.The data is then collected with the device in the image above. The Juno device simply collects satellites then all that the user has to do is click on the map in order to tie the point. Once the point is tied the values pop up in the table which allows for the input of values in to each section. As each point is added to the map they show up on the actual graphic.

Downloading Data:

After all of the data was collected it needed to be imported back to Arc. This process is done by connecting the Juno device to the desktop computer via the transfer cable. The ArcPad manager tab should be opened once ArcMap is open. Once the data is transferred as the .mxd file it should appear into the viewer as an editable map.

Results:

The maps below show the results from the collection of data as a class. Each map shows a different type of data that was collected and symbolized to show variation across the map.

Image 3: The above image shows the dew point values across campus. The highest dew point temperatures were located near the river front across from campus.

Image 4: This image shows the humidity of the air by percentage for each location. The highest humidities were near the new Davies center according to the map above.

Image 5: The map above shows the snow depth in inches on our campus. The greatest depth of snow on the campus was along the river across from campus.

Image 6: The above image shows the temperature gradient across campus. The blue represents cooler temperatures while red and yellow represents warmer temperatures. Once again, the temperatures were higher on the Haas side of campus.

Image 7: The image above was by far the hardest to create. It took me a long time to figure out how to get the arrows to point in the azimuth direction, but it ended up working. In the symbology tab there is an advanced button which allows the user to rotate points via different categories.

Discussion:

This activity was very difficult to accomplish due to the extreme temperature and high winds. In order to get all of the data we often had to have our hands out of our gloves to switch from option to option on the Kestral unit. The area of the campus mall that my group completed was contained within several buildings and the hill that leads to upper campus, so the wind readings that we got varied quite a bit in direction due to a swirling affect caused by the confined space. The most frustrating portion of this lab occurred with handling the Juno GPS device though because at the beginning of the exercise it wasn't getting any satellites, so we did our best to eyeball the points until Professor Hupy came out to help us. There was a technical connection issue within the device where the satellites were turned off. After the device was acquiring satellites the rest of the project ran very smoothly.

Conclusion:

This activity was aggravating at times, but when all was said and done the ending products were phenomenal. The maps that were made did a great job of symbolizing each of the different categories that were collected. The ability to learn how to use the Juno device was also invaluable because it is such a robust tool that allows for GPS interaction and .mxd creation from the handheld device. The Juno device will be used again in this course and is a great tool to understand in general.