Lab 4: Distance Azimuth Survey
Introduction/Background
Lab 4 was an introduction to conducting a Distance Azimuth Survey, and utilizing this survey method as a technique to plot larger-scale geographical sites. This Lab established utilizing tools such as a laser rangefinder to calculate azimuth, a compass to designate potential magnetic field error, GPS to establish coordinates, and a laser distance measurer for furthering azimuth accuracy.
Methods
Site 1:
First, we decided on sites to plot in compliance with the rainy weather; we chose UWEC Phillips courtyard for site 1. Once on site, we first recorded coordinates using a GPS. After we recorded our location, we targeted four different trees in the courtyard and proceeded to measure the degree location of each tree by using the laser rangefinder. In order to maintain accuracy, we had a single person measure from a stationary area. Once our azimuth measurements were recorded, we measured the same three trees with a compass in order to consider magnetic pull. Again, we used a single person to acquire measurements. We then used a laser distance measurer to determine distance between our station and the targeted trees. Finally, we measured tree diameter to include as an extra attribute to our data.
After analyzing the date, we began independently importing the data into ArcPro, but the system would not recognize the csv formatting of the spreadsheet. After attempting different data formats for the file, we decided to try to import the data into ArcMap. With some effort, I managed to import the data as a csv file into ArcMap and started to establish the analysis tools.
After running the Bearing Distance to Line tool, again I experienced error. The lines were there, but they were all vertical.
I wasn't sure why the tool wasn't working, but I was sure it had something to do with our data. I looked for inconsistencies and tried different latitude and longitude outputs, then had an idea to test our GPS coordinates against Google Maps. In opening Google Maps and finding our estimated location, I used these coordinates in our spreadsheet and received a different result entirely.
These results still proved to display inaccuracies. It seems some of our bearing distance lines measured into buildings and into the middle of the parking lot. These data did not mirror our field work and again, I experienced more frustration.
The entire class was experiencing the same issues, so in an answer, Professor Rahman provided us with the data set from a prior class. With these data, I used the Bearing Distance tool to display the distance we measured to each tree, and used azimuth as the bearing input. I also used the Feature Vertices to Points tool which gave the data end points of which I could display another attribute of my choice; for the purposes of our data, I chose tree diameter. These data also seemed to have projection issues, but I created a map with the data to see what I could do.
For the sake of comfort, I began to work with our updated data to further analyze our flaws. This left me with an inaccurate map of our field tree experiment. As you can see below, the tree placements do not comply with the base map.
I didn't like displaying azimuth versus tree diameter, so I started a new map that was more aesthetically pleasing.
Discussion/Challenges
This field activity gave us our fair share of challenges. First, we had to improvise our field stations in accordance to the rainy weather, second, we experienced inconsistencies with our data without knowing what exactly was wrong, and finally, our data could not be accurately displayed in ArcMap even with the coordinate troubleshooting. Our group was not as organized and efficient in this lab which created further room for error. Also, I had a hard time trying to figure out how to most accurately and efficiently display our data in order to make an eye-pleasing and easily read map. I believe the coordinates we acquired from the field lead to the inconsistencies I experienced with ArcMap.
Conclusion
If I were to do this field survey again, I would plan ahead to ensure a smoother activity. We were disorganized, we were not effectively communicating, and our data recording was messy. This type of survey is efficient for plots that are between 0-100 meters because of the techniques and time it takes to measure from field orientation to the object in question. Also, incorporating a consistent GPS measurement is ideal for this type of survey to work.
It is also important to consider the magnetic declination which will vary depending on geographical location. When using tools like a compass, the degree measurements can vary significantly which can lead to a further disorientation of data. Surveyors will rely on a level and laser measurements, like our laser rangefinder, to calculate orientation with precision.
All in all, our results were inaccurate, but I believe the inaccuracies an answer to our methods for acquiring the GPS coordinates. On both sites, we used a mobile phone app to acquire GPS which may have lead to our skewed data presented on the maps.
Lab 4 was an introduction to conducting a Distance Azimuth Survey, and utilizing this survey method as a technique to plot larger-scale geographical sites. This Lab established utilizing tools such as a laser rangefinder to calculate azimuth, a compass to designate potential magnetic field error, GPS to establish coordinates, and a laser distance measurer for furthering azimuth accuracy.
Methods
Site 1:
First, we decided on sites to plot in compliance with the rainy weather; we chose UWEC Phillips courtyard for site 1. Once on site, we first recorded coordinates using a GPS. After we recorded our location, we targeted four different trees in the courtyard and proceeded to measure the degree location of each tree by using the laser rangefinder. In order to maintain accuracy, we had a single person measure from a stationary area. Once our azimuth measurements were recorded, we measured the same three trees with a compass in order to consider magnetic pull. Again, we used a single person to acquire measurements. We then used a laser distance measurer to determine distance between our station and the targeted trees. Finally, we measured tree diameter to include as an extra attribute to our data.
Site 2:
For the second site, we chose to plot on the South side of Phillips Hall. We followed the same procedures, acquiring measurements and data for two trees and a street lamp.
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| Using the laser rangefinder to acquire azimuth of a tree in Site 1. |
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| Distance laser measuring tool. |
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| Comparing our azimuth measurements from the laser rangefinder with our compass calculations on Site 2. |
Data Management:
Once we were back in the lab, we settled all of our data into an Excel spreadsheet with categories displaying our various measurements. We then calculated our compass measurements and compared the azimuth data with the compass. Immediately we saw error between the two different methods.
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| Calculated azimuth for each object location according to compass measurements. |
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| Excel spreadsheet display of our data. |
After analyzing the date, we began independently importing the data into ArcPro, but the system would not recognize the csv formatting of the spreadsheet. After attempting different data formats for the file, we decided to try to import the data into ArcMap. With some effort, I managed to import the data as a csv file into ArcMap and started to establish the analysis tools.
After running the Bearing Distance to Line tool, again I experienced error. The lines were there, but they were all vertical.
 |
| Our original data showing data error in ArcMap. |
I wasn't sure why the tool wasn't working, but I was sure it had something to do with our data. I looked for inconsistencies and tried different latitude and longitude outputs, then had an idea to test our GPS coordinates against Google Maps. In opening Google Maps and finding our estimated location, I used these coordinates in our spreadsheet and received a different result entirely.
 |
| The red bearing distance lines show our old data; the black bearing lines show the updated data with new coordinates. |
The entire class was experiencing the same issues, so in an answer, Professor Rahman provided us with the data set from a prior class. With these data, I used the Bearing Distance tool to display the distance we measured to each tree, and used azimuth as the bearing input. I also used the Feature Vertices to Points tool which gave the data end points of which I could display another attribute of my choice; for the purposes of our data, I chose tree diameter. These data also seemed to have projection issues, but I created a map with the data to see what I could do.
 |
| Map created from a prior class data set. This map showed distance from the field station to particular trees, as well as tree diameter from three different locations. |
For the sake of comfort, I began to work with our updated data to further analyze our flaws. This left me with an inaccurate map of our field tree experiment. As you can see below, the tree placements do not comply with the base map.
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| Azimuth tree map displaying the technical issues we experienced with our data. The azimuth measurements are correct, but some of the distances and station coordinates are incorrect. We can see the data is incorrect with the furthest bearing distance items. |
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| My final map with our field data. This map displays tree diameter in centimeters, as well as distance to the trees in meters. |
Discussion/Challenges
This field activity gave us our fair share of challenges. First, we had to improvise our field stations in accordance to the rainy weather, second, we experienced inconsistencies with our data without knowing what exactly was wrong, and finally, our data could not be accurately displayed in ArcMap even with the coordinate troubleshooting. Our group was not as organized and efficient in this lab which created further room for error. Also, I had a hard time trying to figure out how to most accurately and efficiently display our data in order to make an eye-pleasing and easily read map. I believe the coordinates we acquired from the field lead to the inconsistencies I experienced with ArcMap.
Conclusion
If I were to do this field survey again, I would plan ahead to ensure a smoother activity. We were disorganized, we were not effectively communicating, and our data recording was messy. This type of survey is efficient for plots that are between 0-100 meters because of the techniques and time it takes to measure from field orientation to the object in question. Also, incorporating a consistent GPS measurement is ideal for this type of survey to work.
It is also important to consider the magnetic declination which will vary depending on geographical location. When using tools like a compass, the degree measurements can vary significantly which can lead to a further disorientation of data. Surveyors will rely on a level and laser measurements, like our laser rangefinder, to calculate orientation with precision.
All in all, our results were inaccurate, but I believe the inaccuracies an answer to our methods for acquiring the GPS coordinates. On both sites, we used a mobile phone app to acquire GPS which may have lead to our skewed data presented on the maps.
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