Micro Climate

Charlie Krueger

GEOG 336

Arc Collector Part One: Microclimate

INTRODUCTION

In this lab the class was given the task of gathering data about things like temperature, wind speed, and dew point on campus through a program called Arc Collector. Arc Collector is a program that can be downloaded onto a smartphone or a tablet and allows the user to collect data that will be uploaded to a map in ArcMap Online. Everyone in the class had to create an ArcMap Online account so that the data that was collected could be uploaded to the class map so everyone could access the data. Professor Hupy had already created a map of the study area that the class would be using and dissected that area into five sections so that the data was not all from a small section. The class was separated into groups of two people and then sent into different sections of the study area.

STUDY AREA

The study area that was set by Professor Hupy consisted of the campus of the University of Wisconsin Eau Claire. The study area was separated into five sections so that the groups would get a wide range of data of the area because of the fact that the University does have a wide variety of setting on the campus. There was a section that included the walking bridge and the other side of campus also a section that had the large hill and the area with many dorm buildings in it.

Area of Study divided into the Sections. The section across the river is area 1, to the right of that is area 2, below that is area 3, section 4 is along the river, and section 5 is the farthest to the left. 

METHODS

The methods that were used in this lab were done so with smartphones and a hand held Kestrel 3000 Pocket Weather Meter. The smartphones which had the Arc Collector program on them were used to track the GPS position of the groups as they moved about the campus. Arc Collector was used to plot the point where data was collected and to enter the information that was gathered there. A table would pop up on the app and then things like temperature, dew point, wind speed and direction were entered into the table to then be used later. This data was gathered by using the Kestrel 3000 Pocket Weather Meter which has a small display screen of the information that it is displaying and has arrow buttons to change what is being viewed. Both of these tools were easy to use because smartphones are so widely used in today’s society and the Kestrel was also very easy once Professor Hupy demonstrated with it.

Kestrel 3000 Pocket Weather Meter

            So with both of these tools the groups took off around campus to gather data from all different locations. The group was set into section five of the area of study which was up the hill and around some of the building on campus. Some locations were in the sunshine and blocked by buildings from wind, while others were very windy and in the shade of a building. Certain sections of the study area gave access to different types of environmental features like being over the river to take a wind measurement. Some sections were on top of the hill on the campus which is a very steep incline and had more wind because of the elevation. All the data points and the information taken at those points was sent back to the map in ArcMap online for the class to use the data in making map. The information was saved by each member of the class and then was used to created map that would interpret the data the was gathered and also look for changes on them.

Map of the area with the different groups points in different colors

The information was brought into Arc Map and all that it contained was data points and the information that the class had gathered. From here the data would be placed onto a base map that showed where in the study area the points were taking at. The next step was setting up a mask for the interpolations. This meant creating an outline for the points so that when an interpolation was run it would only use the data from inside that outline. Otherwise the interpolation would not be showing the change of just the data points but of a much larger area where no data had been collected. The final step was running the interpolations for the temperature, dew point, and the wind speed. The interpolation that was used was nearest neighbor which selects the value of the nearest point and then uses that to determine a value for the space. The interpolation spline was not working in Arc Map and gave very strange outputs where nearest neighbor looked to follow the data that was provided.

RESULTS/DISCUSSION

Temperature Change Map

This is the first map that was created from the data and used the temperature that was gathered at the points. The data that was collected shows the how the temperature is different around campus and the minimum and maximum temperature that were found. As the maps indicates the highest temperature was found around the center of the campus. This could be from the lack of wind from the surrounding buildings and the possibility that the points collected were directly in the sun light. The coldest temperatures were found near the very steep hill of the campus which is also surrounded by forest which is shown by the dark blue area of the map. A section that also shows dark red which is high temperature is across the river on campus. This is kind of an outlier but could be because of the exposed area and the sun light hitting that area.

Dew Point Change Map

This was the map that was created from the data collected on dew points. Dew point is the temperature of the atmosphere below which water droplets begin to condense and dew can form. The map shows that the higher dew points were found near on higher elevation. The outlier of this map would be the area in the middle of the upper half of campus, the blue section surrounded by the light yellow area. This area may have been created by inaccurate measuring or by the program that was ran to create the map. There may have not been points here to show that the dew point was closer to the color yellow and not blue.

Wind Speed Map

This was the final map and was created by the wind speed information that was gathered. There are not outliers in this map because the dark red section would be the windiest spots on the campus. The upper campus is usually more windy because of the elevation and even with the buildings there can be very strong gust of winds that funnel between the buildings. The other very windy spot is on the campus walking bridge which is normally very windy because the wind blows right down the river and has nothing in the way to create a wind break.

CONCLUSION:

This lab was successful in showing the changes in temperature, dew points, and wind speed. The data that was collected and then made into maps shows the areas around the campus were these changes happen. Arc Collector was effective for this lab and allowed all of the groups to go into separate areas yet still send data to the same map. It also helped when transporting data in ArcMap because the data was easily downloaded from Arc Online. Overall this lab was a success for the class.