Field Activity #2: Conducting a Distance Azimuth Survey

Introduction

The object of this lab was to be able to gather data points using a distance- azimuth technique rather than rely on standard GPS technology or a large scale grid system. Azimuth is the direction of an object expressed in an angle. Distance-azimuth is another sampling technique that can be used to measure linear or point line data. This lab showed the importance of not relying on technology to make measurements but rather understand the basics to sampling data on a small scale. For this lab 20 deciduous trees in 2 different sites were sampled with this technique in Putnam Park, Eau Claire, WI.

 
Methods

Firstly, data points were needed to be gathered. To do this 2 sites were chosen in Putnam Park about 230 meters southwest from Phillips at 44.795857, -91.501103 coordinates. At each site a reference point was created with a hand held GPS unit in the area of study. Standing in this reference point, trees were picked as samples.

Figure 1. left to right, yellow object- compass, laser distance tool, hand GPS tool.

A compass was then used to calculate the azimuth by looking at which direction it was located (shown in figure 1). The trees distance was measured with a laser distance tool (shown in figure 1). This device used a laser to measure the distance between you (the reference point) to the tree (sample) that was being measured. A measuring tape (shown in figure 2) was then used to measure the circumference of the tree in the same area as the laser distance tool was pointed. 10 trees in each of the sites were picked to give a variation of circumferences, distances, and azimuths. 

Figure 2. Measuring Tapes

Secondly, once all the data was gathered out in the field in a field notebook it had to be inputted into an excel spreadsheet so it could then be imported into ArcMap. All units were converted to centimeters for the most accurate display of measurements. The azimuth had to be calculated because when it was measured, it was in 90 degree increments due to its direction. Using a compass or protractor with 360 degrees one can calculate each data point in respect to its direction i.e. 40 degrees southwest= 220 degrees. A description column was also made to provide the genus of each tree as deciduous shown in Figure 3.

Figure 3. Excel CVS File

Thirdly, the data then had to be imported into ArcMap so it could be mapped. To do this the data was imported as a standalone table to ArcMap, then the Bearing Distance to Line Command tool was used to import the data into a shapefile. This tool is located in Data Management--> Features --> Bearing Distance to Line command. It was then covered to data points from lines using the Feature Vertices to Points command tool. This tool was located in Data Management --> Features --> Vertices to Points command. (Figure 4. Shows the features created from both tools) The GCS assigned to it was WGS 84; however the projection was left alone so it would be projected on the fly with any basemap. A issue came up in attribute table showing more than 20 points. Since a reference point was taken for every site but no azimuth, distance, circumference, or description data was affiliated with it ArcMap created an extra line feature with every tree data point to accommodate for this. To fix this, the Editor tool was used to delete this extra line. However that still left the reference points without any data to map them in this shapefile. A new shapefile was then created and the reference points were exported into it with only the coordinates. This created two separate shapefiles to show data points taken in two different methods. One with a GPS and another with the Azimuth-Distance technique. 

Figure 4. Bearing Distance to Line and Vertices to Points command.

Results/Discussion

Figure 5. Shows the finished map of all the data points taken. The finished product shows a lot of variation in tree size. Interesting enough one can see that most trees with large circumferences are not close to small circumference trees. A concern just looking at this map are the trees located on the trail. Elevation is not taken into consideration in this 1-D map giving the misconceptions of tree locations. If elevation was considered more accurate representation could be recreated. Perhaps using a topographic basemap would show the results more accurately. A large variable that was susceptible to change was the reference point. While sampling multiple trees the reference point could have changed just by human error in moving a couple of cm.

Figure 5. Map of Sample Points taken in Putnam Park, Eau Claire, WI.

Conclusion

This is technique is quite accurate given the minimal amount of technology used to achieve the sample points, however it defaults to human error rather than machine error. Nevertheless understanding the basics to achieving simple data point’s helps in any predicament. Using a GPS provides a easier method to sampling but it is not always the most accurate and knowing the basics help insure one with a solid foundation of knowledge for sampling in any terrain.