Distance Azimuth Survey

Introduction:

For this week’s project we conducted a field survey using a conventional method.  To gather our survey data we used a hand held laser that records both the distance from an object and the azimuth in degrees.  Although there are more accurate methods for gathering this data, you cannot always rely on expensive technology as it often fails.  The device that we used is called a TruPulse 360B manufactured by Laser Technology Inc. This model provides a number of measurement features such as slope distance, inclination, azimuthal direction, and can be synced to data collection software remotely. During the first part of this lab we began familiarizing ourselves with the equipment and processes involved in importing the data into ArcGIS. Later, my colleague and I moved on to survey a 50 meter area within Randall Park.

Methods:

Our class began with a short lesson on the equipment we would be using and the type of data we would be collecting. Two surveying methods were used in our research, a standard compass and a sonar range finder, and a laser range finder with a built in compass. Our objectives were to gather point data using bearing and distance.  Neither of these methods automatically adjusts for the declination angle at your location.  Before surveying any plot of land you must be sure to compensate for the difference between true north and magnetic north.  Luckily for us, Eau Claire is nearly in line with the true north and magnetic north convergence line.  We have approximately one half of a degree of difference making it quite irrelevant when looking at a small 50 meter plot. 

After my partner and I were confident with handling the equipment, we gathered some data points and imported them into the GIS.  This proved to be a rather difficult process and the software was quite temperamental.  It was important to determine the starting location from where you were gathering your data.  We used a base map within ArcGIS to determine our location being sure to give it an accurate projection.  Once our starting point was determined we were able enter it into our data table so that our azimuth and distance recordings were referenced to that point.  Figure 1 shows a sample of test points that were taken in the parking lot behind Phillips hall. It’s important to note that one of our points was not accurately represented within the GIS.  It is always important to check your data’s validity and this would likely have gone unnoticed had we taken a larger sample of points.  The long line extending to the west into the parking lot was supposed to end at the small building about 60 feet to the north.  Since the distance is accurately represented our azimuth recording must have been wrong.

Figure 1: Sample survey points. Notice the left vertices fall approximately 60 feet south of the actual feature being recorded.

After our preliminary survey was done Nick and I moved to Randall Park to conduct our independent survey.  We began by locating an easily identifiable node to record our data. We determined that the sidewalk corner would be easy to distinguish on a projected aerial photo. Our next step was to measure out our 50 meter plot (figure 2).  We decided to record simple nominal data on what type of feature was being recorded (i.e. tree, fire hydrant, stop sign).  The features falling within our measured plot were recorded on a table to be transferred to excel (figure 3).

Figure 2: Measuring our 50 meter plot. We ended up recording features outside of 50 meters to have a larger sample size.

Figure 3: Our data being recorded in the field. The TruePulse 360B comes equipped with bluetooth and can be synced remotely to data collection software. We didn't have a computer with us in the field.

Once all of our data was collected we went on to importing it into the GIS.  This step went much more quickly compared to that of our preliminary survey. After adding the table and exporting it into a geodatabase, we ran the bearing distance to line tool. In figure 4 you can see our data represented as lines extending from a node.  This shows the azimuthal direction of our data as well as the distance represented by the length of the lines. 

Figure 4: Azimuth angles and Distances imported into ArcGIS with an aerial base map.

The next step is to convert the line vertices to points. This tool can be found within ArcToolbox under data management tools, features, and feature vertices to points. Once this tool is run you will now have feature points for the data you collected. After overlaying an aerial photograph you can compare your surveyed features to what is seen in the image.  In figure 5 you can notice that our points fall relatively near the actual features.  A higher quality image would make the image interpretation more clear for example, it is difficult to distinguish a tree from a light post with that low of resolution.

Figure 5: Our data points overlayed on an aerial image. Feature points can be clicked on to view their identification.

 

Discussion:

This exercise provided a relatively simple method of surveying that can be conducted anywhere.  The technology involved was easy to use and the results we gathered were surprisingly accurate.  There were a few points that didn’t quite fall where they were supposed to. This was likely do to some form of human error such as recording the wrong distance. The actual field we were trying to record was too simple. I would have liked to have more fields such as trunk diameter or the tree species. Including this data is what would separate our field study from simply editing point features within the GIS.