Activity #9: Campus Mall Total Station Survey

Introduction

Figure 1 - Learning how to operate the Topcon
Total Station.

This exercise introduced our class to using the Topcon Total Station for doing topographical surveys. Each of our groups were instructed to survey an area roughly a hectare in size of anywhere on campus. Our class meeting on Monday consisted of learning how to set up and use the Total Station. In the classroom, we were shown how to set up and level the tripod and device. Then we went outside to learn how to gather data. From there, it was up to us to find times to meet as groups, check out equipment, and complete the survey.

The Total Station works by shooting a laser at a prism that is on top of a pole. The prism reflects the laser back and the Total Station can determine the location and topographical elevation by the angle of the laser and the time it took to travel. Typically, one person will hold the pole with the prism on it and one or two people will operate the Total Station. The person with the prism will stand in as many places as necessary to collect enough points.


Equipment

Topcon Total Station (Figure 2)

Figure 2 - Topcon Total Station

Topcon GMS-2

Figure 3 - Topcon GMS - 2

TruePulse 360 Laser Rangefinder

Figure 4 - TruePulse 360 Laser Rangefinder

Survey Area

Figure 5 - Location of UW- Eau Claire and study area.

Our group decided to do the new UWEC campus mall for our survey area (Figures 5 and 6). The aerial images are not up-to-date. The building within the red box in figure 6 was demolished and a new one constructed south of that location. The area within the red box is currently a grassy area with stone benches.

Originally, we wanted to do the same area of campus that we did for the distance azimuth survey. This area was too small and too crowded to do an effective survey, however. The campus mall is a wide open area that is more conducive to learning how to do our first survey.

The assignment called for surveying an area a hectare in size (100m x 100m). The area, however, did not get 100m in the north-south direction, so we extended the area east-west that we surveyed to get roughly the same area of coverage.

Figure 6 - Study area on campus. There are not yet any current
aerial images of campus. The area within the red box is an open,
grassy area with rock benches.

The following images (Figures 7- 10) are pictures of our study area.

Figure 7 - Facing north/northeast towards Schofield Hall

Figure 8 - Facing west/northwest towards McIntyre Library

Figure 9 - Facing southeast towards Roosevelt Ave.

Figure 10 - Facing southwest towards the Davies Center.

Methods

Figure 11 - Example of Total Station tripod setup.

To begin the survey, our group needed to set up and level the tripod as well as the Total Station itself. This would ensure that our measurements were accurate. The tripod legs need to be spaced equally apart and have a wide base to ensure stability (Figure 11).

Figure 12 - Leveling screw and circular level.

Next, the Total station can be placed on the tripod and screwed onto the top. Once the device is attached, it's time to level. There are two different areas to level: the circular level and the plate level. The circular level is calibrated by adjusting the length of the legs of the tripod until the bubble is in the center of the circle (Figure 12).

Figure 13 - Plate level.

Next is the plate level (Figure 13). There are three screws near the base of the device that can fine-tune the plate level (Figure 12). To get the bubble in the center of the plate level, face the device between two of the screws, turn one until the bubble is in the middle, then rotate the device to be in-between the next screws. Keep doing this until the bubble stays in the center of the plate level.

Figure 14 - Leveled Total Station ready to collect
data.

Once this step is done, both levels should be calibrated. Figure 14 shows a leveled, ready-to-go Total Station. The height of both the Total Station and the pole holding the prism are also measured and will be entered later.

First we used the GMS to gather a point directly below the Total Station. This would be used as our occupied point. The occupied point is the point that all the other data is collected from. If we have the location of this point, then everything we gather should be accurate (similar to the distance azimuth assignment we did earlier). We then had to set our backsight. We did this by using the TruPulse to find the azimuth to our backsight and label it as such in the GMS. We were then ready to start collecting data.

Figure 15 - Jeremy using the GMS to collect the points while I sight the
Total Station. Zach is circled in red holding the prism at the collection point.

For data collection, one of us held the pole with the prism at the point where data was being collected, one of us sighted using the Total Station, and the third group member used the GMS to record the data (Figure 15). We started in the corner of our study area nearest the library to the northwest and moved back and forth working our way towards the Total Station, then past it, to the southeast portion of our study area (Figure 16). Figure 16 also shows the points that we collected, 147 in total.

Figure 16 - The survey points that we collected, as well as arrows showing the direction and method of point collection.

Results

Our results seemed to be pretty accurate. It is difficult to tell in the figure 17 map (the aerial images are not up to date, so the Davies Center as well as Little Niagara Creek are not shown in the correct locations), but the area of lower elevation is where the campus mall slopes down to the creek. The rest of the survey area, while varying slightly, was mostly level.

Figure 17 - Results of survey interpolated using the Nearest Neighbor method. Range of elevation is from 236.263 - 239.263 meters above sea level.

Discussion

The difficult part of this exercise was setting up the total station. Our professor came out with us when we went to do the survey to show us how to navigate the menus and set up the device. The actual data collection was simple and just a matter of doing the same thing 147 times. The largest issue we encountered (and from talking with others, we weren't the only group that did) was that the Bluetooth connection from the Total Station to the GMS kept disconnecting. This was pretty frustrating, and we never really found out why this was happening. We just had to go back into the settings, reconnect, and continue.

We had intended to switch off roles so everyone got some experience with each, but we realized that the survey went quicker if we each did the same thing for the duration. We were able to get into a good rhythm that way, instead of trading off and having to get into a new rhythm each time. Also, when we leveled the Total Station, we did not take into account that the three of us are different heights. I started off as the one sighting through the device, and I am the shortest one in the group. Zach is much taller than I, and it would have been uncomfortable for him to have to bend over the whole time. We could have adjusted the station, but that also would have taken more time. While it was mostly sunny that day, there was a chilly wind. We decided to not break our momentum and finish the project as quickly as possible.

Luckily, we had no issues when exporting the data to the computer. It went smoothly, as did interpolation and map creation.

Conclusion

The results, while accurate, are a little boring to look at. There is only about a 3 meter range between the highest and lowest point, meaning the survey area was pretty level. This worked out well since we all were using this technology for the first time. Learning would have been slightly more difficult had we had a very diverse terrain. But a slightly greater elevation range would have at least made the resulting map more satisfying.

Terrain surveying is something that is always needed in various different work sectors. I like having a general understanding of the processes, but I hope to gain more knowledge in the future. When surveying larger plots and more dynamic terrain, the Total Station would have to be moved, adding extra steps to the process. This activity was only a brief introduction to land surveying.

Activity #8: Campus Microclimates

Introduction

In Activity #6, we created the geodatabase, domains, and feature class that we would be using for Activity #8. In this activity, groups of two were assigned different parts of campus and were tasked with collecting various weather related data. After the data was collected, we were to combine the data from all the groups, analyse it, and make several maps showing the different microclimates all over campus. The original goal was for each group to collect 50 points, each containing the predetermined information we decided on during Activity #6. Due to time constraints, equipment problems, and cold weather, most groups were not able to gather the full 50 points. We utilized what would could.

Study Area

Figure 1 - Study area for the different groups. My group's
study area is in the red box and our classroom is in the
purple box.

The first thing we had to do was divide up the parts of campus that each group was responsible for. We did this by simply allowing groups to pick, so first-come-first-serve. My partner and I did not speak up very quickly, and so ended up with a study area relatively far away from the building we had class in. Figure 1 shows the different groups and where their study area was located. Zach Howard and I were group 4, and our study area is withing the red rectangle. The purple rectangle is Phillips Hall, where our class meets every Monday.

Figure 2 - Our group's study area - field and parking lot
west of Haas Fine Arts Center

Figure 2 shows a close-up of our study area. This area lies to the west of the Haas Fine Arts Center. Our area included a grass (mostly snow covered at the time) field and a parking lot that had Water Street to the north and the bike trail and Chippewa River to the south.







Below are some pictures from our study area:

Figure 3 - Open field west of Haas Fine Arts Center, looking north.

Figure 4 - West side of Haas Fine Arts Center, looking northeast
from approximately same position as in figure 3.

Figure 5 - Parking lot to the west of field, from approximately
same position as figures 3 and 4.

Figure 6 - Parking lot south of the field, camera facing
southeast.

Figure 7 - Parking lot west of field, camera facing northwest.

Methods

Exporting Geodatabase

Figure 8 - Feature class and background raster in ArcMap

Before we could start gathering data, we needed to get the geodatabase, complete with domains and feature classes, prepped and onto the GPS device. Before exporting to the device, it's important to get the map ready so that it can easily be used in the field. We already had domains and a feature class created from Activity #6, but we also wanted a background image. Using an aerial image of campus as a base map, we brought everything into an ArcMap file (Figure 8).

Figure 9 - Image extent used when exporting to GPS device

Since our group would only be using our study area from this image, I zoomed to the field by Haas Fine Arts and made sure that when I exported the data to the GPS device, it would only be our study area, as opposed to the full image (Figure 9). At this point, it would be a good idea to double check that the domains and feature classes are properly set up before exporting (especially in this case since it has been a few weeks since I created them). We forgot this step, and thus had to manually fix the attribute table after we finished collecting data (more on this later). ALWAYS DOUBLE CHECK!

Figure 10 - Extensions menu where we select
ArcPad Data Manager

In order to export the map, a couple of things must be done within ArcMap. Under the Customize menu on the main tool bar, click on Extensions. Extensions are "add-ons" to ArcMap that usually cost more to have access to. The ArcPad Data Manager is one such extension that we will need access to. In this menu, we can check the boxes next  to any extensions we may need (Figure 10). Luckily, UWEC has access to all of them. Once we have access to ArcPad Data Manager options, we can add the toolbar. Once again under the Customize menu, select Toolbars and then ArcPad Data Manager (Figure 11) and the toolbar shown in figure 12 will pop up.

Figure 11 - How to add the ArcPad Data Manager toolbar

Figure 12 - The ArcPad Data Manager toolbar

Clicking the first icon on the left (with the arrow point to the right) opens the menu for choosing what data we want to export. The list automatically brings up the data that is on the current map. Where it says Action, click and choose Checkout all Geodatabase layers. The window should look like it does in figure 13. The next window is where we specify output options. I set the folder to export the data to (a previously created folder within my class folder on the network) and named the folder that would store the data micro_haasta_howardza (micro + both of our usernames) (Figure 14). Lastly, in deployment options (Figure 15), I made sure the box next to Create the ArcPad data on this computer now was checked. 

Figure 13 - Get data for ArcPad window

Figure 14 - Output options for data

Figure 15 - Last step in ArcPad data creation 

Figure 16 - Two copies of ArcPad data, in case a backup is needed

It may take a few minutes to create the data. Once it is complete, the data will be in the folder specified. Before moving ahead, copy-and-past this folder so that there is backup data in the event of any problems (Figure 16).

Figure 17 - Timble Juno
3 series

For this exercise, we are using the Trimble Juno GPS device (Figure 17). The device connects using a simple USB chord. Once it is connected, all that we need to do is cut-and-past one of the ArcPad data folders (in my case, micro_haasta_howardza) into the GPS device's storage using Windows Explorer.





Gathering Field Data

Once the geodatabase was on the Trimble, we were ready to head outside and collect the data. We brought several devices and tools (Figure 18) to help with this process. Here's the list:

Figure 18 - Equipment Zach and I used to collect data

1.) Trimble Juno GPS
2.) Kestrel 3000 weather meter
3.) Folding measuring stick
4.) Bandanna
5.) Orienteering compass









Once outside, it did actually take us a while before we were able to start collecting data. Neither of us were very familiar with using the Trimble Juno, and it took some time to get it working properly. After getting help from both Professor Hupy and Martin Goettl (the geography department's GeoSpatial Technology Facilitator), we found out that TerraSync (Trimble's GPS software that is also on the device) was also open. Only one program can be acquiring satellites on the device at a time, which is why ArcPad wasn't working.

When we got to our study area, we starting collecting points. For each point that was collected, we entered the following data:

Time
Temperature (degrees F)
Wind direction (azimuth)
Wind direction (cardinal)
Wind speed (mph)
Dewpoint (degrees F)
Relative humidity
Snow depth (inches)

When creating the domains, I had set the Group domain as being coded values. I either forgot to enter the codes, or they didn't save. Either way, I wasn't able to enter our group number until after we exported the collected data back to the computer. This wasn't that difficult, since '4' was the entry for every point, but had it been any other field, it would have been another setback. This is why you should always double check your domains before sending the geodatabase to your GPS device. This will avoid problems in the field.

Temperature, wind speed, dewpoint, and relative humidity could all be found using the Kestrel. All that was necessary was to scroll through the different features using the arrow buttons. The measuring stick was used to measure snow depth. Many of our points didn't have snow, as about half of our study area was parking lot, and much of the winter snow had melted by this point. The bandanna was used to find the wind direction azimuth. We could hold up the bandanna by a corner and hold the compass under it to get a general idea of wind direction. For the time, I simply used the time shown on my cell phone.

One of us would take measurements using the trimble, measuring stick, Kestrel, and compass/bandanna, while the other person plotted GPS points and recorded the information called out by the other. Zach and I switched off roles about every 10 points. This was partially so we could each get practice doing both, but also because our hands would get very cold doing the same thing for too long. In the end, we were only able to collect 27 points since class ended at 6:00 P.M.

Checking-in Data from Trimble Device

When we got back to the class room, we had to export our newly collected data from the GPS device to the computer. This was pretty simple. The Trimble was plugged back into the computer using the USB chord. Using Windows Explorer again, I navigated to the folder I created before going out into the field (micro_haasta_howardza, now with our fresh data) and cut-and-pasted it back into my personal class folder.

In ArcMap, we simply did the opposite of what we did when sending data to the Trimble. On the ArcPad Data Manager toolbar (again, make sure the ArcPad Data Manager extension is turned on), click the Get data from ArcPad button (Figure 19). Make sure you have the correct folder selected and click Check In.

Figure 19 - Check in data from ArcPad

In order to create maps and analyse the data, the shapefiles created by each group needed to be combined into one shapefile. One of my classmates was nice enough to do this by merging all seven of the separate shapefiles into one, and providing the result to the rest of the class to use.

Results

Figure 20 shows temperature data for my group's study area only. Warmer temperatures are on the north end of the parking lot, and are cooler to the south. This could be because of more shade closer to the bike path. There was more shaded areas from trees in that area, where as there was more exposure to sunlight closer to Water St. The black asphault could have been radiating more heat, as compared to the field that was also in the open. The ground was snow covered in those areas.

Figure 20 - Map showing distribution of temperatures for Group 4 study area
(using IDW interpolation method).

Figure 21 shows the temperature data for the entire class. There is one very high temperature in the middle of campus, which is why I used Natural Breaks classification for this map instead of a equal interval like I did in figure 20. This way, the outlier did effect the data.

Figure 21 - Map showing distribution of temperatures for campus using
data from all groups. Created using Nearest Neighbor interpolation method
and Natural Breaks (Jenks) classification.

Figure 22 shows the wind data. Each arrow points in the direction that the wind is blowing to and is color-coded to represent wind speed. The day that we collected data was not very windy in general, though there were some gusts.

Figure 22 - Map showing wind speed and direction for class data.

Figure 23 is a TIN (Triangulated Irregular Network) that shows snow depth around campus.

Figure 23 - Map of TIN showing snow depth around campus.

Discussion

The snow had started to melt before we collected the data, so that is why areas of higher snow depth seem concentrated. The areas where snow depth is highest is in the middle of campus. I would guess that this is simply from snow being plowed off of the sidewalks and pilling up, as opposed to actual snow accumulation depth. The other area where snow depth is deepest is down by the river, which makes sense.

The wind map in figure 22 and the temperature map in figure 21 seem to show that areas with higher wind tended to have lower temperatures. On upper campus where there was generally stronger winds (probably because it is out of the valley) had lower temperatures than much of campus. The area behind and around the residence halls on lower campus had very low winds (significant cover from buildings), and had higher temperatures (in general). Our study area (by Haas Fine Arts) had higher winds AND higher temperatures. This could be because our location was exposed more to the sun (and wind) than other areas on campus, and had parking lot asphalt reflecting the energy.

The one very high temperature in the middle of campus (81.8) was puzzling. There could have been ventilation from the nearby building, or simply operator error. Also, several points from one of the groups displayed on the equator. This could have been because of proximity to buildings and subsequent lose of satellite connection. But those errors did have to be removed so that data analysis could be done properly.

Conclusion

It was interesting to see just how different some of these variables are from one place on campus to another. It would have been better (though colder) to do it on a day when there was more wind. Since most wind speeds were below 4 mph, the differences shown on the map are not very conclusive. We also had to work together for this project; not just in our groups, but as a class to consolidate the data in a usable manner. I thought this went well, with people sharing the information with the rest of the class when they could. I general, I liked this assignment. I just wish spring would come already so I didn't have to be distracted by frozen fingers during every field exercise.

Activity #7: UAS Field Day

Class on March 10th was the first break in the record cold winter since the semester started, so Professor Hupy made a last minute decision to get outside. Instead of a project or assignment, we took advantage of the beautiful day (temps into the 50s) by meeting at the Eau Claire Sports Center to test out different forms of UASs. We saw two different rotary copters, a kite, and a rocket; all with cameras attached. Max, who is a physics student at UWEC, was assisting Professor Hupy with flying and calibrating his copter as well as demonstrating his own copter that he is building for a senior project. The kite was interesting because I have never seen a 'real' kite (by that I mean one that wasn't $2 from K-mart with cartoons on it) before and wasn't aware they could support the weight of a camera. This would be relatively cheap, and a form of UAS that I could afford to do on my own. The rocket was fun to watch, despite not working properly. Professor Hupy taped two key-chain cameras (around $10, light weight, and take video) to the rocket that faced down, so that they would take video of the flight. Unfortunately, one of the rocket's engines was put in upside down. The rocket did not achieve much height, and the parachute did not launch (probably because not enough gas filled the tube from only one engine igniting). Either way, we got to see some UASs in action as well as experiment with video from a rocket and spend the day outside. Here are some pictures of the day.

Figure 1 - Professor Hupy's Multicopter

Figure 2 - Carload full of goodies.

Figure 3 - Max's Multicopter

                                       

Figure 4 - A big kite.

Figure 5 - Professor Hupy attaching the camera to the kite.

Figure 6 - Kite in flight.

Figure 7 - Professor Hupy building a bomb...
I mean rocket. A science rocket.

Figure 8 - It's for science, honest.

Figure 9 - Rocket on launch pad.

Figure 10 - Professor Hupy taping the cameras
to the science rocket.

Video - Launch of science rocket.