Conducting a Distance Azimuth Survey

INTRODUCTION
Survey technology has dramatically improved in the last few decades.  Surveyors have a variety of tools at their disposal that allow for increased accuracy and efficiency, but sometimes technologies can fail.  In this activity we used a range finder and compass to conduct a distance azimuth survey.  The devices we used can come in handy when other resources are not available.  Our study area consisted of a 1/4 hectare plot on the new campus mall at the University of Wisconsin-Eau Claire.

METHODS
OBJECTIVE I

The first objective of this activity was to familiarize ourselves with the tools.  I worked with a partner, Phil, throughout the entire project.  We went outside behind Phillips Hall at the University of Wisconsin-Eau Claire and used a laser range finder as well as a compass to collect distance and azimuth of trees in the area. The distance was taken in meters and the azimuth was taken in degrees.  We recorded the point data in a notebook.

After we had become familiar with both devices, we used Microsoft Excel to create a table of our point data.  The initial fields were simply "SD" (Slope Distance) and "AZ" (Azimuth).  We imported this table into a file geodatabase and added it to a blank ArcMap document.  Because we did not use a GPS unit to collect the X and Y coordinates of our origin point, we had to add an aerial basemap and locate our position.  When I located our origin location, I used editor to add an X and Y field in our table.

The next step was to use the "Bearing Distance to Line" tool in ArcToolbox in the Data Management-Features folder. This tool creates a new feature class with line features calculated by the X and Y locations, the bearing field (AZ) and the distance field (SD).  After completing that process, I used the "Feature Vertices to Points" tool located in the same folder as the previous tool.  This tool creates a point feature class from the vertices of the newly created line feature class.  These new points represented the location of the data points (trees) that we collected.  To my dismay, the tree data points were located miles from the actual site location.  After some troubleshooting, Phil and I realized that our origin coordinates were not specific enough for accurate representation.  To overcome this, we changed the Data Frame Properties in ArcMap so the Display Units were decimal degrees.  I then used the Identify tool to click on the origin points on the aerial image.  This gave me X and Y coordinates with 6 decimal places, which was specific enough to accurately represent our data points.  The slope distance and azimuth are represented by the blue lines and the trees are represented as the lighter blue circles in Figure 1.

Figure 1-Test data represented in ArcMap

OBJECTIVE 1
After we had become familiar with the range finder as well as functioning in ArcMap, Phil and I conducted another distance azimuth survey.  This time, we collected data points for the stone benches located in the new campus mall.  We used two origin points, the steps of the library and steps on the south side of Schofield Hall.  The benches were located in a somewhat large area with a south-western slope.  By using to origin points, we could ensure the accuracy of the slope distance and azimuth angle.

Again we used the range finder to collect the Slope Distance (SD) and Azimuth (AZ) for each bench.  When the range finder could no longer accurately measure the SD and AZ of the benches, we moved to the steps of Scholfield Hall.  While collected the data, we had to keep a close eye to make sure we did not skip benches or collected benches twice.  We wrote the SD and AZ measurements in a notebook while collected the data and then transferred this data into an Excel spreadsheet.

Because I had run into errors on our previous attempt to import the spreadsheet into ArcMap, I created ID, X and Y fields directly into the spreadsheet.  I opened ArcMap and used the Identify tool to locate the X and Y coordinates of our origin locations (Figure 2).  This data was then pasted into the spreadsheet in the corresponding fields.  The ID field was generated simply by assigning a number in numerical order to each data point (Figure 3).

Figure 2-Identify tool in ArcMap

Figure 3- Excel spreadsheet for
bench data points

Once the Excel table was normalized, the table was imported into ArcMap and the "Bearing Distance to Line" tool was implemented (Figure 4).  After the new feature class was created, the "Feature Vertices to Points" tool was used (Figure 5).  This created a point for each bench we had collected.

Figure 4- Bearing Distance to Line tool

Figure 5- Feature Vertices to Points tool

The following images show the transformations of the data from a blank aerial image to the bearing distance line data and finally to point data, the final representation of our data points, benches in the new campus mall.  The old Davies Center on campus was removed in the previous summer, but the aerial image does not show that.  In reality, the benches exist on an open courtyard.

Figure 6- Blank aerial image of study area

Figure 7-Bearing distance lines from origins

Figure 8-Point data; Final data representation

DISCUSSION
Although these tools are beneficial when technology isn't available, there are still downfalls to this technique.  When hand-eye coordination is essential to the accuracy of a tool, human error can occur.  In this activity, we had to hold the laser range finder with one hand while aiming at the benches to record the SD and AZ.  The measurements were quite accurate, but some distortion will always accompany such methods.

Another error that can occur in this method is the duplication of information.  Below are images that seem to show this error, but the scale of the map had to be changed to show that the data points did not overlap (Figures 9, 10, 11, 12).

Figure 9-Image showing a zoomed out view
with overlapping data points

Figure 10-Image showing a close up of the
data with no overlapping data points

One must know how to overcome magnetic declination while taking a distance-azimuth survey.  Magnetic declination is the angle between true north and magnetic north which changes over time and differs on location.  Complex algorithms must be used to calculate the magnetic north because it is constantly changing.  It is necessary to know, calculate and use magnetic north while using a compass, otherwise angles could be very skewed.

CONCLUSION
This survey taught me the possibilities of somewhat simple data collectors like a compass of laser range finder.  Technology can fail in one way or another; knowing how to collect data with alternative resources is very important in the geospatial realm.  Distance-Azimuth surveys are also beneficial because sometimes extreme technology isn't needed to collect data and create an informational product.  The skills learned in this activity can be applied in a vast array of ways and can be applied to a variety of different formats.