Topographic Survey

Introduction :
This week our task was to create a Topographic Survey of the UWEC campus using a survey grade GPS. at various points around campus, which would capture the make up of the campus grounds.


Study Area/Methods:
As per usual the study area was the UWEC campus grounds (Fig 1), which does have a large variety of terrain and geospatial features, such as the campus mall, which is a flood plain, the banks of the meandering Chippewa river (not pictured) and Little Niagara Creek which flows through the campus mall.   

Fig 1. The UWEC Lower Campus, and the study area of the Topographic Survey.

We deployed a survey grade GPS to capture points of the UWEC campus. The survey GPS we were using had two components a top receiver and a TESLA unit that is a mobile field tablet controller

Fig 2. The Topcon Survey Grade GPS and Tablet Receiver being explained by Dr. Hupy.

After turning on both components of the GPS, we began collecting points. We had to make sure that the points which we were collecting were fixed, and that the accuracy in both height and vertical distance was at a usable minimum, in this case, under one meter of variance.




Fig 3. The GPS Unit showing fixed position and height (H) and vertical distance (V) error estimates, as you can see both estimates come in under 1 meter.

Once an object was going to be surveyed, we would select the point type from a prearranged list of objects on the UWEC campus such as light posts, garbage cans, bus stops, etc.. This points can really be anything that one wants to survey, but obviously have to be applicable.

Fig 4. List of objects to choose from when surveying.

Once the object was established as our survey point, we set the survey grade GPS as close as possible to a point that we were trying to capture and input the type of object it was, and if the object was tree, we recorded the diameter at breast height (DBH) measurement of the trunk. We had the GPS capture a minimum of 20 points at that location, each having a slight variation in height and vertical distance variation as the GPS captured data. Then the GPS averaged all the variation in height and vertical distance that were measured into a final point that was reported. For increased accuracy one could have the GPS record more points.

After many points were captured we brought the data into ArcMap simply by taking the text file the data was reported in, and importing that to a table in a new geodatabase. From there we imported the points using the "Add XY data" tool on that table and then defining the fields of the table.

Results/Discussion:

Once the points were entered and uploaded to ArcMap, they were mapped with the results are listed below. In terms of representing the points, all of the points were in the correct position relative to the base map (Fig 5), with points appearing to be out of place like in the distance azimuth survey.

Fig 5. The UWEC Campus with all of the points surveyed displayed on a map showing the positions of points surveyed (green) in relation to the rest of campus.

Because this survey was capturing attribute data on different objects on campus a symbol map listing each one was appropriate (Fig 6). As a survey would gain complexity by increasing the size and scope of the project, a different tactic may need to be taken in representing all of the point attributes that are captured, such as grouping features for easier representation, which was not necessary here.

Fig 6. A closer extent of the points surveyed on near Phillips Hall, with colors indicating the object surveyed.

In an attempt to better represent the points different symbols were employed to try and bring a little more depth to the map/ make the map more appealing to the average viewer (Fig 7).

Fig 7. Getting fancy with the symbolism of the Topographical survey.

With a photograph of campus as a basemap, some of the points suffered from being undistinguished due to the contrast ratio between the colors in symbols and the tree coverage of campus (Fig 7). So a new base map, which turned out to be more updated with actual representations of the current buildings on campus was used instead. With out the tree coverage and the lack cars, the points of the survey are represented better.

Fig 8. In the above base image layer, I noticed that the representation of campus was outdated, so I searched for a new one. While not as pleasing as a photo, it is accurate to where the actual buildings on campus are.

Conclusions:

As compared to the distance azimuth survey which was relativistic in its point determination, the topographic survey with a survey grade GPS was excellent in its ability to capture data points accurately.  All of the points appear to extremely accurate and are not located in positions where they physically can not be, which is to be expected considering that each point was captured with a survey grade GPS 20 times and then averaged to create a single point. Due to the accuracy level of the equipment employed this topographical survey did a much better job of representing points on campus as compared to the distance/azimuth survey.

But realistically, the distance/azimuth survey is not for the same purpose as a topographical survey such as we have just done. A survey grade GPS is an expensive piece of equipment which is used in industry analysis, construction, and situations where accuracy truly matters. The distance azimuth survey is employed where very limited situation constraints exist and one needs to be more adaptive in their survey methods.

Another important note is that error and in accuracy can still occur when using expensive equipment. A survey grade GPS for example is accurate, but also evolves the skill of the user and that persons ability to under stand not to understand the equipment but the theory behind how that equipment gathers data to get the most out of the survey. While the only error that can occur in a survey like this is human error in either setting up the GPS or in integrating the points into ArcMap, the error can still be costly, and requires the human component to think through the process and understand the limitations of the technology behind the unit.