Conducting a Distance Azimuth Survey

Introduction

    The purpose of this lab is to become familiar with creating a survey using direction and distance. Sometimes while in the field technology is going to fail. Sometimes a GPS will run out of batteries or will not be able to acquire a signal due to heavy forest overgrowth, for example. In this case it is important to be able to collect data points using semi-archaic methods. Therefore, we will be using distance and azimuth measurements to plot the location of vehicles, and some associated attributes, in the Phillips parking lot (Figure 1). The Phillips parking lot is the most commonly used parking lot on campus and is constantly full. It contains about 90 faculty parking spots, 40 guaranteed faculty spots, 144 student parking spots, and 19 spots reserved for visiting future Blugolds.

Figure 1 Aerial image of Phillips Lot located on the University of Wisconsin- Eau Claire campus.

Methods

    To begin this exercise we had to decide on some features that were to be collected. Since we had to collect 100 points, we decided to survey the one thing that was readily available, vehicles. We set up the TruPulse 360 laser on the corner of the parking lot and started collecting the horizontal distance in meters and azimuth to individual vehicles parked in the Phillips lot. We also collected two attributes for each vehicle, the type of vehicle and the color. After collecting data for 68 different vehicles in the first location we were unable to collect any more. This caused us to move to a second location outside of Phillips Hall near the "art" by the entrance to the courtyard (Figure 2). After the data was collected for all 100 vehicles we came into the lab and entered it into an Excel table (Table 1).

Figure 2  TruPulse 300 setup used to complete the vehicle survey.

Table 1  Sample of attributes collected using the TruPulse 300 distance/azimuth finder.

    The next step in the process is to use the Bearing Distance tool to create lines to each of the vehicles based on distance and direction. At first, I had some difficulty getting the tool to work correctly. After some frustration I decided to take another approach. I altered the Excel table to only include the x,y coordinates of the TruPulse laser points, the horizontal distance, and the azimuth (Table 2). After this new table was created I imported it into the distance azimuth geodatabase and added it to the ArcMap display. We then opened the Bearing Distance to Line tool and inputted the variables into the tool (Figure 3).

Table 2  Altered table that was input into the Bearing Distance to Line tool.

Figure 3  Bearing Distance to Line tool interface.

    After the tool was finished running it left us with lines based on direction and distance to each vehicle we surveyed (Figure 4).

Figure 4  Lines created showing the location of cars based on distance and azimuth.

    After the line feature class we created I joined to original table containing all the vehicle attributes to the altered table that was used in the tool (Table 3). This will allow us to create a map showing where the different vehicle types and colors are located.

Table 3  Original table joined to the altered table in order to map the attributes of each survey point collected.

    After the distance azimuth lines were created and the tables were joined together I ran the Feature Vertices to Points tool (Figure ) to create a point feature class of all the vehicle locations (Figure 5). 

Figure 5 Feature Vertices to Points tool interface used to create point locations of each of the vehicles surveyed.

Figure 5 Point locations of each vehicle surveyed.

    Combining the lines and points created into one map we can show the location of vehicle colors and what type of vehicle is present at each location. As you can see from the graphs below, 25% of the total vehicles surveyed are silver in color (Graph 1) and 54% of the vehicles are cars (Graph 2).

Figure 6  Map showing the color and type of each vehicle surveyed.

    Then, I ran the summarize tool in ArcMap to produce a table that gives a count field for each of the vehicle types and colors. I imported those summary tables into Excel and created a graph showing the number of vehicles by color (Graph 3) and the number of vehicles by type (Graph 2). 

Graph 1 Number of vehicles surveyed based on color.

Graph2  Number of vehicles surveyed based on vehicle type.

 Discussion

    As previously stated, the method of surveying using distance and azimuth is a fairly good method when extremely accurate results aren't necessary. After the data was collected I noticed two major errors that affected the location of the survey points. The first error was the inexact x,y coordinates being used. Not having the exact x,y coordinates causes that location of the TruPulse laser to be moved from its actual position. Figure 6 shows that location of the x,y coordinates that were input into the Bearing Distance to Line tool compared to the actual position of the laser.

   

Figure 6 Actual location of TruPulse 360 compared to the GPS location.

 Another source of error associated with azimuth is the magnetic declination at a particular location. Magnetic declination is defined as the angular difference between magnetic north (the direction a compass needle points) and geographic north (the direction perpendicular to the equator). Some areas of the world have up to 30 degrees of magnetic declination. However, in Eau Claire, WI the magnetic declination is only 1.05 degrees to the west. Therefore, in this distance azimuth survey all of the points plotted must be moved 1.05 degrees to the west. This error can be seen in Figure 7, where the location of the points are located east of where they were actually located in real life. 

Figure 7  Errors associated with the TruPulse 360 that are caused by magnetic declination

    While the location of the x,y coordinates or the magnetic declination may be causing errors in the data, there may also be other factors causing the points to not show up in the correct locations. I recently noticed, while collecting GPS data for another class, that this particular aerial image may not be orthorectified properly. During this GPS collection the points collected on the east side of Phillips Hall were constantly being placed about two feet west of the sidewalk even though we were collecting the points from the middle of the sidewalk. If the aerial is not orthorectified accurately, the survey data collected in this lab may actually be correct.

Conclusion

    In conclusion, there are many highly scientific ways of plotting survey points, such as survey grade GPS units. However, there are certain situations that high tech equipment will not work or may not be needed. In this case it is very important to understand how to use simpler methods to achieve a fairly accurate survey. A basic survey, as done above, can also be conducted using only a compass for direction and paces to estimate the distance to each individual point. Obviously, this method would not be nearly as accurate as using a distance finder. Therefore, one needs to know the overall project accuracy in order to determine which method is necessary.