Lab 3: Conducting a Distance Azimuth Survey

Introduction

What will happen if you need to conduct a survey using a fancy GPS and survey stations when the technology fails? Or maybe you are going to a different country and Customs cease your equipment for investigation.  It was not all that long ago that humanity did not have this kind of technology and they seemed to survive just fine. In order for us to combat this metaphorical issue we used a tool which could calculate the distance between you and the object as well as calculate the azimuth.

Using a sophisticated Trupulse Laser Range Finder, we could point to any object we wanted and in turn the range finder would give us multiple values, the only ones we were interested in were slope distance (SD) and azimuth.

Study Areas

For this lab we used four different study areas. The first study area used was done in class as a way of testing the equipment out. On the southeast side of Phillips Science Hall located where the access road meets the back parking lot (44.796281,-91.499395) Figure 1. The class shot a series of points to get a better grasp of how this equipment worked. My group (myself and Zachary Nemeth) shot six points from this location.

Figure 1: Study Area 1- Done during class time, Results-Failed

The second study area we used was located on the northeast side of Phillips Science Hall located by the bus stop at the circular drop off point for vehicles (44.797638,-91.498991) Figure 2 and 3. We shot a total of 20 points from this location. Our features included trash cans, black street lights, wooden street lights and silver street lights.

Figure 2: Study Area 2: Facing Campus we collected Street lights and garbage cans from this location

Figure 2: Study Area 2, reverse direction: Here we collected several different street pole types

The third study area we used was located in the campus mall. Choosing the large circle located in the large open area of the mall because of its easily identifiable properties on a map (44.79782,-91.500787) Figure 4. At this location we shot a total of 51 points (bringing out total to 71). We shot presumably every stone located in the amphitheater and recorded them as either single stone, double stones or triple stones depending on how many were grouped together.

Figure 4: Study Area 3: Campus Amphitheater, here we collected data on all of the stone seats (single, double and triple)

Our final study area was located about 20 feet away from the northeast corner of Schofield Hall (44.798761,-91.499713) Figure 5. Here we shot our remaining 29 points to bring our total number of points shot to an astonishing 100 points, taking about an hour to do so. At this location we shot a variety of objects including benches, trash cans and assorted lamp posts (and came across one person who called us weird because they thought we were spying on people). 

Figure 5: Study Area 4: Here we captured several benches and light poles

Each of the study areas chosen all served a purpose, we wanted to pick areas that were relatively open and away from buildings, that way when we put the points on a map they are all going to be spread out and not have 15 points all in a straight line looking one direction. The features we chose to shoot, we wanted something you could see on a map, that way we could see how precise our data was.

Methods

All of our data points we collected using a Trupulse Range Finder (Figure 6). The first step was to acquire this piece of equipment from the UWEC Geography Department. Once acquired, we went off to each of our three study areas listed above in the study areas section of the blog. We had a slight idea in our minds of what we wanted to shoot, but would not make up the decision until after we got to our location on what else we could shoot. 

Figure 6: Trupulse Range Finder, equipment used during data gathering

Once at the study area, we would use the Trupulse Range Finder and look through the scope. Through the view finder there was a square cross hair type of image on the lens, this is what you would line up with what you were trying to find the distance and azimuth of. Once the desired object is in the cross-hairs we hit a small button on the top side of the range finder labeled FIRE. This would cause a laser pulse to shoot out and gather data of the object. Using the arrows on the side of the range finder to scroll through the data we found the slope distance and azimuth of the desired object. One person would be using the range finder and saying the distance and azimuth (as well as the object being shot) while the other person recorded the data into a google spreadsheet (Figure 7). This would be repeated 99 more times. 

Figure 7: Document containing all the information gathered from the field

The next step was to find the exact coordinates of each of our three starting locations. This was done using Google Maps and right clicking on the exact area of study. An option would pop up saying “What is here” and clicking that would give us the X and Y coordinates to the 6^th decimal place. We put that information into our Google Spreadsheet and then copied and pasted the entire sheet into Excel. We did this so we could work with the data in ESRI ArcMap.

In a geodatabase already created in ArcMap, right click and scroll down to import and select table (single). After doing this our data was imported to ArcMap and was ready to be used. The first tool we had to use was called Bearing Distance to Line Tool (Figure 8 and 9). This tool would give a list of options to choose from including X, Y, azimuth and distance options which had to be filled out properly in order for this section to work. 

Figure 8: Bearing Distance To Line tool will give us the lines from the starting point to the feature point

Figure 9: End result from running the Bearing Distance to Line tool

The next step after this was to take those vertices and make them points. This step requires the Feature Vertices to Point Tool (Figure 10 and 11). For this tool there is only three options. Input Features, which is our feature we just created in the previous step, Output feature class, which is for saving purposes and lastly Point Type. For this category make sure to select END for the option otherwise you will end up with double the number of points, since it will take both the start and ending points.

Figure 10: Feature Vertices to Points will give the points at the end of the lines

Figure 11: The end result of using the Feature Vertices to Points tool, layered over the previously ran tool

In order to make it possible to show what each point represents we have to join the points with our Excel file. This is a simple join based on the Object ID. After running the join, I created a map showing the three study areas and what each line was pointing to represented as a different color (figure 12).

Figure 12: Final product of feature points. 

Step Recap

1. Gather Trupulse Range Finder

2. Locate Study Area

3. Use Trupulse Range Finder on desired objects

4. Record data in Spreadsheet

5. Record coordinates of starting locations

6. Import data in Excel Spreadsheet

7. Import data into ArcMap Geodatabase

8. Use Bearing Distance to Line tool in ArcMap

9. Use Feature Vertices to Point tool in ArcMap

10. Join the points feature class with the table by Object ID

11. Create visual pleasing maps

Discussion

On our map we had three different study areas, mentioned above. Two of the three study areas proved to be pretty accurate, but the campus mall Amphitheater one seemed to be off by several degrees. When we were testing the equipment earlier in the week we found that underground wires and Wi-Fi signals could be distorting the sensor. Here I believe that is the issue. All of the points, when looking at the map, seem to be off by about 15-20 degrees and about 3 feet short of the target. The other two study areas went off without a hitch.

In order to rid of any biasness we kept the same person capturing the data through the range finder and the other person kept to typing the data.

Unfortunately, the most recent imagery used shows Centennial Hall still being constructed. This lead to several points looking like they were construction equipment and not the light posts or tables that our actually there today.

Overall we spent about an hour collecting data points in the field. It was around 8am when we started so some points were hard to see, especially ones which were east of us, looking through a range finder when the sun is in direct line of your object is not fun, and incredibly dangerous if done for too long.

Frequently Asked Questions

Q: What am I looking for while scrolling through the range finder?

A: There are 2 different fields we are looking for one is labeled SD meaning Slope Distance, Slope distance takes into account the vertical and horizontal distance of the objects. The second set we are looking for is labeled AZ. This is the azimuth or how many degrees 0-360 we are away from True North. 0/360 would be north, 90 east, 180 south and 270 west.

Q:  What happens if I use the ALL point type on Feature Vertices to Points tool

A: It will double the number of points you have. Instead of just calculating the end points, which is what we wanted to do in this lab, it will calculate the start and end point resulting in 100 features become 200. This will then throw off the table join, resulting in 50 of your points not having a feature description.

Q: There is no current base map with up to data UWEC imagery?

A: In order to combat this issue, I used two images from the Geospatial folder on the UWEC Geography Departments Servers. Although it is not completely up to date, it still gave me what I needed, something the other base layer data could not give me, unless I was zoomed way out.

Results

The image above shows the final product of all the study areas. In total we tagged 6 benches (red), 19 black street lights (orange), 2 cigarette receptacles (light orange), 9 double stones (yellow), 8 Silver Street Lights (green), 34 single stones (blue), 11 trash cans (purple), 8 triple stones (pink) and 3 wooden street lights (grey).

Although we were careful with the data collection, we still had a little skewness to our data. Again this could be contributed to just about anything. It could be from Wi-Fi, or underground cable wires, or it was hazy and foggy during our time of data capturing, there is an infinite number of possibilities which could skew the laser, even human error was a possibility.

Conclusion

Overall, this is a pretty low tech form of mapping features. We were of course using a very expensive tool for this, but it could easily be done using a ruler tape and compass. That would have taken us a lot longer than the one hour we spent outside collecting data though.

This could come in handy if GPS technology is unavailable or if something happened to your equipment making it no longer usable. Although in a world with ever growing technology this tool, range/azimuth finder, has been replaced by far more sophisticated technologies which can easily take out the human error.