ArcCollecter and Micro Climates

Introduction
     This lab used ArcCollecter to gather data remotely in the field and transfer it into the Esri online web service. This method of data collection is exceptionally powerful because it allows for multiple people to gather data in various locations at the same time and upload it to the same online document. This lab looks at the micro climate for the University of Wisconsin - Eau Claire, specifically the temperature, dew point, wind speed, and wind direction. For this lab the class was broken up into 9 different groups and assigned different locations around campus where the groups gathered the weather attributes. Figure 1 below shows the campus of the University of Wisconsin - Eau Claire broken up into 5 different zones. The author of this post collected data from zone three. The terrain for zone 3 was a mix of woods, bog, and

 (Figure 1: A map of the 5 different zones that were mapped out for the micro climate lab)

the campus itself. The area in the eastern half of zone three is woods that has a small creek, called the Little Niagara, traveling threw it, Little Niagara travels all the way threw zone 3 then cuts north through zone 4 until it hits the Chippewa River. Certain areas around the creek have turned into a bog or wetlands, these terrains are solely located in the eastern half of zone 3. The western half of zone 3 contains the campus science building, the student union, and the nursing building. The terrain around these buildings is well kept with trees planted artistically around the buildings. Other notable terrains in the study area include the area between zones 5 and 3/4, which is a wooded hill with a very drastic elevation change. The southern portion of zone 1 is the flood plains and also contains a slight elevation change from the water to inland. The northern portion of zone 5 is Putnum park, Putnum Park is on a cliff that overlooks the Chippewa River and is very wooded. Little Niagara discharges into the Chippewa in Putnum Park.
   

Methods
     In order to measure the different weather attributes around the Eau Claire campus different tools were used. The main tool to measure the weather was a Kestrel weather meter, which is able to measure the wind speed, temperature, and dew point, to name a few of the functions. A compass was used to find the direction that the wind was blowing in degrees. The final tool was a smart phone with GPS capabilities that had the ArcCollecter app downloaded. This app allow the user to access their esri online profile from their phone and collect GPS data points.
     Every group had a smart phone and were assigned a zone in which to collect the weather measurements. These points would then be uploaded to a pre-created basemap of the area that was provided by the professor, Dr. Joe Hupy. After all the points were collected each person was able to download the online maps to a desktop version of ArcMaps and use the field data. This lab called for surface maps of every attribute mentioned above. The inverse distance weighted interpolation method was used to create a surface maps of the attributes collected. Wind direction was a special case, instead of creating a surface map the GPS symbols were turned to arrows and rotated to face the direction that the wind was blowing. These arrows were overlayed on the wind speed surface map.

Results
     Below are all of the surface maps that were created. The first image, Figure 1, shows surface temperature map for the Eau Claire campus. This map is particularly interesting due to the patterns that formed. The Pink blobs in the south eastern portion of the map represent hot spots where the temperature was between 63 and 64 degrees Fahrenheit. These three building represent the where the student union, science building, and nursing buildings are located. Another hot spot is in the north which represents the Eau Claire arts center. The green areas to the east of there represent cold spots. These cold spots represent the wetlands in the woods where sunlight was reduced, lowering the temperature.

(Figure 2: Surface Temperature Map of the Eau Claire campus)

 
     Figure 3 show the dew point surface map. This map shows an obvious pattern where a diagonal area of higher dew point separates 2 different areas of lower dew points. This is caused, in part, by the Little Niagara which follow the path of high dew points. Also the forest ridges follows this same path and can also be a cause the higher dew points.

  (Figure 3: Surface Dew Point Map for the Eau Claire campus)

 
     The final map is the wind direction and wind speed map, which was briefly explained above. Figure 4 is an image of this map. The wooded ridge is a huge factor to wind speed and direction. There is a green path, which represents wind speeds between 0 to 2.2 mph, that follows the ridge line. The areas above and below have significantly higher wind speeds than the areas around the ridge. There are lower wind speeds in the north eastern corner as well. This could due to the surrounding houses and trees blocking the wind.

(Figure 4: Wind speed and wind direction surface map of the Eau Claire campus)

Conclusion

     This project was an excellent success. The data transfer from every ones phones to the online Esri mapping site went very smoothly. Having multiple people collecting data points simultaneously saved a considerable amount of time and was overall more efficient. ArcCollecter is an amazing resource that is significantly cheaper and more accurate than most GPS units. Also it makes getting the data from the field to ArcMaps quick and easy. It would be unsurprising if smart phones and ArcCollecter replace most GPS units in the very near future.