Field Navigation Part Three

Use of handheld GPS units for field navigation.

Introduction:

Over the last two weeks our group, Andrew Peterson, Amy Bartel and I have completed two separate exercises associated with land navigation; those exercises included the use of available data and resources to create a navigation map, and using that map to do traditional land navigation using the map and a compass. The navigation exercise was done at the Priory and the immediate surrounding area. The Priory is located approximately 5 kilometers south of the University of Wisconsin Eau Claire (UWEC) campus on Priory Road. Directions to the Priory from UWEC are as follows. From the main campus area take Roosevelt Avenue east to State Street, turn right on State Street and follow it south until you come to Lowes Creek Road, turn right on West Lowes Creek Road, you will cross over Interstate 94 then come to Priory Road, turn right on Priory Road and watch for the sign for the Priory on your right. For this week’s exercise we used modern technology (handheld GPS units) to navigate another portion of the area surrounding the Priory locating several points along the way.

Methods:

For this week we were not allowed to use a map to aid in our navigation. We were restricted to the use of handheld GPS units and given the coordinates of the points we were to locate (figure 1). The point locations were given in UTM NAD 83 coordinates. Our GPS units were also set at UTM. Again, there were three courses, each consisting of six points, to navigate and six teams navigating. One team on each course navigated the course forward (1,2,3) while the other team navigated the course in the reverse order (6,5,4).  Our group was to navigate the second course in the reverse order.

Fig.1. During this exercise we used a handheld GPS unit to
navigate to several points on one of three courses set up at
the  Priory, in Eau Claire, WI.

We began by starting a track log on the GPS to record our movements throughout the exercise. In order to locate a point we first checked the point coordinates of the point we wanted to navigate to, then we observed our coordinates on the GPS unit. Now the tricky part, we first had to get ourselves moving in the correct direction. In order to figure this out we had to ‘wander around’ a bit and figure out which way was which and get our bearings in relation to the point we wanted to navigate to. After we had a general idea of which direction we wanted to travel in we began to walk in that general direction, while walking we had to continue to watch our location on the GPS to be sure that we continued in the correct direction, adjusting our travel according to the easting and northing on the GPS (figure 2).  After we located a point we would repeat this process for each consecutive point until we finished the six point course. At the conclusion of the course we stopped the track log.

Fig.2. While navigating the course we had to
 maintain constant interaction with our GPS units in order to keep our bearings. 

After the exercise we downloaded our track logs using DNR Garmin software. We connected the units to a computer using the USB cable supplied then opened the Garmin program. We clicked on track and download. After the data were downloaded we went to file and save to our file as a shape file. Then in Arccatalog we import the shapefile to our geodatabase as a feature class and projected it in UTM, which we also saved into the Priory geodatabase for use by other students for their mapping. I added the locations of all of the points around the Priory to my existing map and then added my tracklog and created a map representing myself (figure 3). I then added the tracklogs of my teammates to the map and created a map of our combined efforts to locate our six points (figure 4). I gave each team member an individual color and shape to distinguish one from another.  Finally, I added all the available track logs from my classmates to the map in group layers. Each group was given a unique color and each member of the group was given one of three symbols, these same symbols were used for all groups. Then I finished with a map of the class’s efforts during this exercise.    

Fig.3. Map of the Priory with Stacy Camren's track log. There was a lot
of 'wandering' during this exercise. 

Fig.4. Map of the Priory with all of the track logs from the members
of my group. Note two track together and one separate from the
others, one member was late and had to navigate the course without
 the other two members.

Fig.5. Map of the Priory with all available track logs from the class.
There is at least one track (black) that does not seem to fit any of the
 courses, it was also not clearly identified in the geodatabase as to who's
track it was. 

Discussion:

There were several challenges this week; the first was getting our entire team together. One member of the team was late and we were forced to begin without them. Because of this we did not actually see the other member of our team until we were finished. The second challenge worth mentioning is both the new snow and the amount of snow present. The new snow was clinging to the trees very heavily and in some instances may have reduced the effectiveness of our GPS units by blocking or reducing satellite reception (figure 6). The amount of snow present made it incredibly difficult to walk in areas where there was a combination of a steep slope and snow cover that was more than knee deep (figure 7).

Fig.6. There was several inches of new snow , much of it
was still clinging to the tree branches and may have reduced
the accuracy of the GPS units.

Fig.7. Much of the area was covered with snow that was knee
deep and deeper making it very difficult to travel in.

The last of the large challenges was using the GPS to locate the UTM point coordinates. While navigating from point to point you naturally do not walk in a straight line. This can be cause by many things such as one leg being slightly longer or stronger than the other, or even the Coriolis Effect. But much of our deviation over these short distances was caused simply by obstructions such as trees, brush or in one instance a fence that had to be navigated around (figure 8). The difficulty was every time we made a directional change, either on purpose or not, we had to figure out what our bearing to our point should be again. This resulted in very inefficient direction of travel and a lot of misdirection; however, we did not have to be as precise when navigating around obstacles.

Fig.8. There were some areas that you are
forced to navigate around due to trees and
brush.

Overall we finished the course much faster than we did with traditional methods. Traditional methods used much more time to prepare and required more cooperation between individuals, however if done well traditional methods were much more direct.    

Conclusion:

It appears to me that each of these methods may have an appropriate use depending on time and manpower. Between these two I would choose to use traditional land navigation because of its simplicity and directness and the fact that I am comfortable with this method. If possible it would make sense to use both technologies simultaneously. It also would have made a difference to insert the navigation points as waypoints and navigate directly to them.

Field Navigation Part Two

Use of a compass and map for field navigation

Introduction:

Last week our group, Andrew Peterson, Amy Bartel and I, used available data and resources to create a navigation map. This map included the Priory and the immediate surrounding area. The Priory is located approximately 5 kilometers south of the University of Wisconsin Eau Claire (UWEC) campus on Priory Road. Directions to the Priory from UWEC are as follows. From the main campus area take Roosevelt Avenue east to State Street, turn right on State Street and follow it south until you come to Lowes Creek Road, turn right on West Lowes Creek Road, you will cross over Interstate 94 then come to Priory Road, turn right on Priory Road and watch for the sign for the Priory on your right. Now that we have a usable map and we are at the location the map covers,; how do we use the map to navigate and what are we navigating to?

Methods:

After arriving at the Priory each group was given a list of coordinates (table 1) to points located in the area surrounding the Priory. At each of these points there was a numbered flag with a related paper punch denoting that flag and location. The flags were arranged to produce three individual navigation courses consisting of six locations each. As a class we had six groups of three people each. With only three courses, three of the groups would navigate the courses beginning to end while the other three groups would navigate the courses from the end to the beginning. Our group was assigned to the first course and would navigate it backwards.

Point #	Latitude	Longitude	UTM Y	UTM X	Altitude
1	44.76487	-91.51319	4957906	617662	313
2	44.76573	-91.51378	4958001	617614	301
3	44.76716	-91.5141	4958159	617585	255
4	44.76939	-91.51164	4958410	617775	260
5	44.76804	-91.51072	4958011	617970	278
6	44.76443	-91.51118	4957860	617822	297

  Table.1. Point number, coordinates and altitude for the six points 

  located on the first course. Two groups navigated this course, one 

  navigated the course in numerical order while the other navigated it 

  in reverse order.

The first step to navigating the course was to locate the points on the map. Our map had a UTM grid in place and we were provided with both Latitude and Longitude and UTM coordinates of the points (figure 1). To place the points we followed our grid with its labeled x-y coordinates and transferred the points from table 1 to the map (figure 2), our grid was set at 20 meter intervals so there was some interpolation to gain the most accurate position on the map. At each of the six points we marked the point with a permanent marker, this helped keep the marks visible during inclement weather, and labeled them.

Fig.1. This is the map we produced for use in this exercise.
The map contains and aerial image of the Priory, 5 meter
topographic lines, the search area we were constrained to
and a UTM grid overlay.

Fig.2. We are using the coordinates from table one to
plot our way-points  on our map of the Priory.

Now that we had our points plotted and we knew what direction we would be navigating in we could figure out our bearings from point to point and the distance between the points (table 2). To do this we used a map compass. The compass we used was my Brunton type 7. This compass allows you to utilize the grid on the map to set the compass to north after which you can simply read the azimuth bearing. OK  it is a bit more involved than that.

Points	Bearing	Distance (meters)
1 to 6	105	165
6 to 5	47	210
5 to 4	334	445
4 to 3	218	310
3 to 2	172	160
2 to 1	153	110

 Table.2. These are our point pairs and 

  their bearing and distance measures.

To gather the azimuth bearings from the map we begin by placing the long edge of the compass baseplate on the map using it to connect one navigation point to another one pair at a time, in our case we began by connecting point one with point six. We had to be sure the direction of travel arrow always pointed in the direction we wanted to move (figure 3), our point order was 1-6-5-4-3-2-1. Failure to do this could result in traveling the opposite direction we wanted. After lining up two of the points we turn our attention to the housing of the compass. The housing contains the actual needle and a series of parallel lines (orientating lines) in the bottom of the housing. In the North side of the compass housing there are also marks used to adjust for magnetic declination. In the Eau Claire area we have already determined the declination to be approximately 58 minutes west which is minimal enough that for the scale of this exercise we did not worry about it. We turned the housing until the orientating lines ran parallel to the north/south UTM lines on the map (figure 3). This was also critical; the orientation lines are bi-color black and red, red faces north and black faces south. The housing must have the red portion of the lines and the north arrow facing north on the map failure to do this could again lead to navigating in the wrong direction. After we lined up the edge of the compass between two points on the map and adjusted the housing to point north we were able to read our azimuth bearing. The numbers that run around the dial are azimuth. Located under the dial at the direction of travel arrow is an index mark, the number immediately over this mark is the azimuth for our direction of travel from point to point (figure 4). We repeated this process for each of the pairs of points on the map. Two of the sets of points were longer than the compass so we used straight edge from point to point and held the edge of the compass along it. To get the distances between each of the points we used the scale on the map and measured the distance from point to point.

Fig.3. This is a simulation of the UTM grid on our map. This was
done to clearly show how the orientation lines match the north/south
grid lines, the red portion of the lines and the north arrow are directed
north in concert with the map. Also note the orientation of the compass
in the direction of travel from point 1 to point 2. 

Fig.4. Here we can see the index mark beneath the dial of the
compass. The index mark is concurrent with the bearing arrow
on the base of the compass.  The sample bearing here is 148 degrees. 

For the field navigation we use the azimuth bearing we previously determined and the point to point distance. The three members of our group volunteered to each do a job navigating, the jobs were using the compass to determine our bearing (Stacy), pace the distance from point to point (Andrew)and to assist in determining the direction of travel (Amy). This worked well because we each had strong points. Andrew and Amy’s pace counts were very specific and did not very over several trials, and I had previous experience using a compass to navigate. To navigate from point to point we began using the compass to determine the direction of travel. I stood at point one and rotated the housing of the compass until our bearing for the pair of points was at the index mark on the compass housing. Then, holding the compass out in front of me with the direction of travel arrow pointed away from me, turned my body and the compass as one until the red portion of the arrow (north) was within the orienting arrow, also red, inside the housing. An easy way to remember this is “red Fred in the shed”. Once we achieved this we can look across the compass in our direction of travel. Just as when we were using the compass on the map we had to be sure the compass pointed in the direction of travel and that the red portion and north faced north or we would not be navigating in the correct direction. After we got our bearing Amy would walk out in that direction as far as she was able to while maintain a clear line of site with me (figure 5). When she got as far as she could go I would communicate with her verbally if she was close enough or using hand signals to get her as precisely in line as we were able. Then using the distance measured on the map and dividing it by 100 meters then multiplying it by Andrews pace count we could determine the approximate number of paces to the next point. Andrew would pace to Amy (figure 6) and we would repeat this process until we were at or in the vicinity of the point we were looking for. After reaching each of the points we would use the available punch to mark our card, evidence that we found the point (figure 7). Then we would continue on to the next point.

Fig.5. Amy is getting set on our bearing. At this particular spot
the large White Pine was directly in our path. In order to get
around it I had Amy go to the far side and hold her arms out so
I could estimate better where her body center was for our reset.
Andrew is aiding in communication. 

Fig.6. Andrew is pacing to Amy, the process of extending our
bearing and pacing our distance was performed until we reached
our next point.

Fig.7. Amy is using the punch at point two to mark our card.

Discussion:

We encountered several issues while plotting the points. The first was our grid, as instructed we used a universal transverse mercator (UTM) grid on the map. UTM will work with a global positioning system (GPS) system but not so well with a map and compass. Because we were using a compass and magnetic north we should have used a Geographic Coordinate System instead. However, this was not a large issue do the large scale of our map and the relatively short distances we were covering. The second issue was with our choice of marker used to mark the points on the map. We used a basic marker with a wide tip which does not allow for a very precise point, a Sharpie marker would work much better. When gathering the distance and azimuth data for the points we had to give it our best guess as to the actual point on the map. This may have influenced our readings slightly. We also had to account for the fact that when we tested for our pace count we were on flat level and clean ground, during the navigation exercise we were in knee deep snow traveling up and down steep hills. Much of the difference was accounted for by adding paces to the distance, not very precise though.

We were able to successfully navigate from point one to point six a distance of 165 meters. We were off by about 20 feet at point six. From point six to point five a distance of 210 meters, we were right on and had no issues. From point five to point four a distance of 445 meters we were not successful. This stretch contained areas with a very high density of brush and trees which in concert with the large hills caused us to make repeated calculations at short distances. Each time we had to reset we open the door for greater error in our navigation. This combined with the possible errors discussed earlier caused us to miss our target by about 35-40 meters. The time involved in the numerous resetting also limited us to only finding the three points. We were unable to finish the course as we were rapidly losing daylight.  

Conclusion:

This was a great exercise utilizing a very low tech tool, the compass, to do fairly accurate field navigation. Personally, I have used similar techniques to triangulate the position of radio collared animals. By using a radio antenna to get the direction of an animal from your position on a road and reversing the procedure described above  you transfer the bearings from your position to the animal onto a map. you would do this from at least three different points. Where the bearing lines cross each other is the approximate location of the animal. I enjoyed reinforcing those skills and techniques while getting to rummage around in the outdoors.

  

Field Navigation Part One

Construction of a map for use in field navigation.

Introduction:

For the next two weeks we are working on one project, Field Navigation. This project has been split into two smaller projects; the first is to create a map for use in the actual field navigation exercise, and the second is to use the map to navigate a plot of land and locate several items along the way. The plot of land we will be navigating is known as the Priory. The Priory is located approximately 5 kilometers south of the University of Wisconsin Eau Claire (UWEC) campus on Priory Road. Directions to the Priory from UWEC are as follows. From the main campus area take Roosevelt Avenue east to State Street, turn right on State Street and follow it south until you come to Lowes Creek Road, turn right on West Lowes Creek Road, you will cross over Interstate 94 then come to Priory Road, turn right on Priory Road and watch for the sign for the Priory on your right.

Methods:

Pace count is used in navigating, by knowing how much distance you cover with each stride you can estimate distance covered on the ground on a map. We  began by going outside and measuring out 100 meters using the True Pulse 360 B (figures 1,2), and then walking that distance repeatedly (figure 3). In doing so we were able to get an average pace count over that distance and estimate the distance we cover with each stride. My pace count was 69. With each two step pace I cover about 1.5 meters. Knowing this we can use the map to estimate distance to an object then use our pace to put that distance on the ground. We will use this in the navigation portion of the exercise next week.

Fig.1. One student walked out down the sidewalk while another
used her position to measure out 100 meters using the True Pulse.
   

Fig.2. Amy using the True Pulse to range the distance
of the student walking away on the sidewalk,  looking for
a distance of 100 meters.

Fig.3. Students walking 100 meters to get their pace count.

Construction of the map was done using Arcmap and Arccatalog. In Arccatalog I created a file geodatabase for navigation. Then I explored an assortment of data that was located on the university system in a geodatabase for the Priory. After looking at the data available I decided I wanted to keep the map fairly simple yet have usable information on it. I chose to use a color aerial image of the area of interest (AOI) which shows buildings and the overall lay of the land but also shows the varying vegetation types. I also chose to include a data set of 5 meter topographic lines. This data was obtained from the United States Geological Survey (USGS), as a 1/3 arc second digital elevation model (DEM).This is not a very precise data set, at 5 meters, but it gives a general flow of the topography in the area. The combination of the topographic data and the areal imagery should be very effective for compass navigation.

In Arccatalog, using the data located within the Priory Geodatabase, I used the toolbox and the clip tool to clip the data sets being used and save them into my navigation geodatabase. To accomplish this I used a polygon feature class which covers an area just larger than the property at the Priory. After the data was clipped and saved into my geodatabase I also copied the polygon feature class used to clip the data and another containing the actual property.

In Arcmap I set the work space projection to UTM Zone 15N, then had to use the project tool to project the polygons layers into UTM Zone 15N, and used the project raster tool to project the aerial image also. I layered the map with the aerial image on the bottom then the topographic lines over that. I included the search area, layered over the others, as a guide to limit our coverage during our navigation. Both the search area and the topographic layers were given bright colors to stand out against the background of the map. To aid in the navigation process I added a grid over all other areas. The grid is also set to UTM Zone 15N. The grid was added by going to the properties of the data frame then selecting grids. Select add new grid and finish the process. After the grid was been added I went back to the grid properties and adjusted the format to show lines at 20 meter intervals, label the edges so they were all readable when the map was held upright, and adjust the labels to only show the labels we wanted, the others were reduced font and given a light color.

I finished by adding a scale, a simple legend containing the search area and topographic lines, and a compass arrow designating north. These were each given backgrounds so they were easily distinguishable from the rest of the map. I also added the data sources, map projection, the name of the map maker and the date the map was produced. This was also given a background to make them more visible to the reader. the final map will be used in the field navigation exercise next week (figure 4). 

Fig.4. This is the completed map for use in the field navigation exercise. The map includes a base of aerial imagery
of the Priory, 5 meter topographic delineations, and the search area surrounding the Priory. A UTM grid at 20 meters was layered over the map to assist with navigation. All data layers were projected in NAD 83 UTM Zone 15N. 

    

Discussion:

While analyzing the data in Arccatalog I observed the projections of the data. All data that I used was projected into the same coordinate system to minimize troubles with data matching between layers. The data that was not used included 2 meter topography. This data was stored as a DRG file and many encountered trouble with the projection of it in Arcmap. The data had to be brought into the data frame in a specific order because the data frame will take the projection of the first item brought in. I chose not to use this data because it made the map to busy. There were too many lines for such a small area however a different project may have warranted the use of such data. We also had some aerial images that had higher resolution than what I used; however these were grey scale images and didn't show the vegetation as well as the color image. The color image was taken either in the late fall or early spring meaning the environmental conditions of the vegetation were very similar to what they are now in early March allowing for groups of vegetation to be easily distinguishable. Had we been doing this later in the summer the gray scale images may have been better.      

Conclusion:

For this project I found it useful to think about what the conditions were at this time of the year and what we were trying to accomplish. Using this information I made what I believe to be the best choice in data selection giving us a clear map with usable data and not over filling it with data we would not use or that would be impractical.   

Distance and Azimuth Surveys

Using electronic and non-electronic methods to conduct distance and azimuth surveys.

Introduction:

Our objective for this week was to work as part of a two person team using different methods to gather point data including distance and azimuth. I was partnered with Amy Bartel. The data we gathered was then loaded into a Geographic Information System (GIS) mapped and examined for accuracy. Methods to gather data included the use of low tech compass to gather azimuth data, and range finder to gather distance data; and a more advanced True Pulse laser range finder which gathers distance and azimuth data at the same time.

We gathered our data on two separate dates and at two separate locations (figure 1). The first location was on Monday, 18 February 2013 at the University of Wisconsin Eau Claire (UWEC), Eau Claire, Wisconsin. We gathered data on several objects and trees that are located between the south edge of the Phillips Science Building and the north edge Phillips parking lot. This location was convenient for the time available and the number of objects present to record data for. The data for the second location were gathered on Friday, 22 February 2013 at Randall Park, located two blocks north of Water Street in Eau Claire, Wisconsin, just blocks from the UWEC campus. For this portion of the project we were to gather data from an area of ¼ hectare plot and include at least 50 points. The location of this park made it a convenient walk from campus it also contained enough points for our project. The park, however, is larger than ¼ hectare. I used the measuring tool in Google Earth to get the size of the park; the distance from sidewalk to side walk is approximately 82 meters by 142 meters, just over one hectare. This was necessary to gather the required number of points.

Fig. 1. This image shows a portion of Eau Claire, WI. Randall
Park and the Phillips Science Building on the UWEC campus
have been highlighted along with the location of Water Street. 

Methods:

Preparation for this include going to the State cartographers website, (http://www.sco.wisc.edu/mapping-topics/magnetic-declination.html) where I found a link to the National Geophysical Data Center (NGDC) part of the National Oceanic and Atmospheric Administration (NOAA). The NGDC webpage has a calculator to compute your declination. You will need the latitude and longitude of your study location. If you do not know your latitude and longitude you can enter your zip code and click the get location button. The calculator gives your latitude and longitude; if you know them you can just enter them. Then you enter the correct date and click the compute declination button. The website gives you the magnetic declination for your area. In Eau Claire, Wisconsin the magnetic declination is 0°58’. We had to adjust our instruments for the declination.

We used a compass and sonic range finder to locate several point within a narrow strip between the Phillips Science Building and the Phillips parking lot. I took azimuth readings with a compass and operated the acoustic range finder while recording the data in a notebook. Amy walked to the points being recorded with the receiver. We used a small tree near the south-east corner of the building as our origin; this should be visible from aerial images. After recording the data for several points we created an excel spread sheet with the headings (attributes): point_number, X, Y, distance, azimuth, and notes (table 1). Point number was simply the 1^st, 2^nd, 3^rd… points we recorded. Distance and azimuth were what we measured. To get the X and Y data we used aerial imagery in ArcGIS.

point_number	x	y	distance	azimuth	notes
1	-91.499610	44.796492	9.69	107	blood
2	-91.499610	44.796492	7.93	140	cone
3	-91.499610	44.796492	19.06	136	tree
4	-91.499610	44.796492	22.8	135.5	tree
5	-91.499610	44.796492	14.85	151	phone
6	-91.499610	44.796492	10.79	265	tree
7	-91.499610	44.796492	19.74	271	tree
8	-91.499610	44.796492	34.67	281	tree
9	-91.499610	44.796492	44.05	285	tree
10	-91.499610	44.796492	54.58	287	building

 Table.1. This data from the first survey was entered into excel then imported into Arcmap for analysis.

After opening Arcmap we set the data frame projection to a Geographic Coordinate System (GCS) World Geodetic System (WGS) 84, this will allow us to work with latitude and longitude. Then we loaded a base map from World Imagery and zoomed in to our area of interest (AOI). In the image we located the tree we measured from and using the identify tool found the coordinates of the tree (-91.499610, 44.796492). These coordinates were put into the excel file as X and Y for all of the points since we gathered them all from the same location. We opened Arccatalog and created a new file geodatabase (GDB), we imported our excel file into the GDB then in Arcmap using Arccatalog input the data into the data frame. Using the toolbox in Arcmap we opened Data Management, and then Features. Within features is a tool called Bearing Distance to Line. We used this tool to import our data as a layer in the form of lines from the point of origin to all the points that were recorded. The lines are directionally based on our azimuth readings and the line length is based on our distance measures. Then we used another tool also located in Features called Feature Vertices to Points, again we are able to import the data as a layer however this layer is comprised of points. The points represent the data points that we measured in the field. We now have a map containing a base map layer and point and line layers representing our data (figure 2).

Fig.2. Survey one at Phillips Science Building. The points and lines are
not accurate because: 1, we could not get the accurate location of the tree
trunk we used as our origin; 2, as we measured we moved around the tree
causing our azimuth readings to be skewed.  

During our second data gathering excursion we went to Randall Park. We used a True Pulse 360 B laser range finder made by Laser Technologies Inc. to measure distance and azimuth. The park is quite large but it was necessary to record at least 50 data points for the project. Within the park there are a lot of obstructions, mainly trees. In order to gather all the needed points we used four separate origins located at the four corners of the park.  We began at the south-east corner of the park (figure 3); Amy operated the True Pulse while I recorded the data (figure 4). We had to locate a suitable point of origin that could be located on aerial images. We used the north-west corner of the yellow ‘rumble’ strip on the side walk, the strip contrasts well with the surrounding concrete. From this point of origin we gathered data on 12 points. We then moved to the south-west corner of the park (figure 5), here we used the base of an electric pole as our point of origin and recorded 12 more points. When we moved to the north-west corner of the park Amy and I switched jobs (figure 6), she recorded the data while I operated the range finder. At this corner we again used an existing electric pole as our point of origin and recorded 12 additional points. At the last corner, the north-east corner (figure 7), of the park we gathered the remaining points using the south-west corner of the yellow ‘rumble’ strip in the sidewalk just as we had on the south-east corner (figure 8).

Fig.3. View from the south-east corner of Randall Park.

Fig.4. Amy using the True Pulse to gather
distance and azimuth data from the south-
west corner of Randall Park.

Fig.5. View from the south-west corner of
Randall Park.

Fig.6. Stacy using the True Pulse to gather
distance and azimuth data from the north-
east corner of Randall Park.

Fig.7. View from the north-east corner of
Randall Park, Note the yellow rumble strip
in the foreground of the image.

Fig.8. A corner of the yellow rumble strips used to tie the survey
data to X,Y data gathered from aerial imagery in Arcmap.  

As in the first example we built an excel spreadsheet containing our data with headings: point, X, Y, distance, azimuth and name (table 2). Point was the point number while distance and azimuth were the data we had measured and name was the object at the point we recorded the data for. Object names included a statue, trees, lamp posts, benches, picnic tables and the posts at the corners of a pavilion. We used Arcmap, setting the data frame projection to GCS WGS 84 and located our four points of origin. The rumble strips were easily located because of their contrasting color. The base of the electric poles was determined by first finding the pole and then locating the shadow of the pole on the ground. We used the point where the pole met its shadow as our point of origin. We used the identify tool to get the X and Y coordinates for each of these four points and correctly apply them to the corresponding sets of points in the excel spreadsheet.

point	x	y	distance	azimuth	name
1	-91.505758	44.804196	8.4	292.0	tree
2	-91.505758	44.804196	21.0	318.8	tree
3	-91.505758	44.804196	41.0	327.4	tree
4	-91.505758	44.804196	7.7	0.9	tree
5	-91.505758	44.804196	27.6	350.4	tree
6	-91.505758	44.804196	44.0	336.4	table
7	-91.505758	44.804196	22.3	339.1	tree
8	-91.505758	44.804196	38.5	310.7	lamp
9	-91.505758	44.804196	69.0	305.4	lamp
10	-91.505758	44.804196	91.9	305.0	bench
11	-91.505758	44.804196	86.0	308.2	bench
12	-91.507619	44.804213	127.0	307.0	lamp
13	-91.507619	44.804213	8.9	82.0	tree
14	-91.507619	44.804213	19.0	76.9	tree
15	-91.507619	44.804213	76.0	74.3	statue
16	-91.507619	44.804213	11.0	39.7	tree
17	-91.507619	44.804213	19.8	48.2	tree
18	-91.507619	44.804213	38.5	56.9	lamp
19	-91.507619	44.804213	92.9	62.9	bench
20	-91.507619	44.804213	11.1	38.9	tree
21	-91.507619	44.804213	35.0	29.7	bench
22	-91.507619	44.804213	17.9	18.5	tree
23	-91.507619	44.804213	78.3	57.8	bench
24	-91.507621	44.804952	76.0	84.5	tree
25	-91.507621	44.804952	46.2	128.2	lamp
26	-91.507621	44.804952	26.9	136.0	tree
27	-91.507621	44.804952	10.1	131.5	tree
28	-91.507621	44.804952	24.1	151.1	tree
29	-91.507621	44.804952	92.0	126.1	statue
30	-91.507621	44.804952	83.0	126.2	bench
31	-91.507621	44.804952	53.9	106.6	tree
32	-91.507621	44.804952	13.9	98.4	tree
33	-91.507621	44.804952	39.9	94.1	tree
34	-91.507621	44.804952	53.3	162.1	tree
35	-91.507621	44.804952	84.1	112.4	pavilion
36	-91.507621	44.804952	84.0	113.6	pavilion
37	-91.505759	44.804971	93.9	233.2	statue
38	-91.505759	44.804971	38.0	231.1	lamp
39	-91.505759	44.804971	75.4	243.4	pavilion
40	-91.505759	44.804971	74.5	244.0	pavilion
41	-91.505759	44.804971	36.0	219.8	tree
42	-91.505759	44.804971	11.0	213.8	tree
43	-91.505759	44.804971	26.1	219.4	tree
44	-91.505759	44.804971	22.6	238.7	tree
45	-91.505759	44.804971	42.2	243.3	tree
46	-91.505759	44.804971	32.7	248.5	tree
47	-91.505759	44.804971	48.0	251.9	tree
48	-91.505759	44.804971	14.8	253.9	tree
49	-91.505759	44.804971	23.6	258.9	tree
50	-91.505759	44.804971	28.4	266.3	tree

Table.2. This data from the second survey was used to map 

distance and azimuth lines and object points in Arcmap.

We returned to the GDB in Arccatalog that we set up earlier and imported the new spreadsheet. We opened the environments and set the work space defaults to our GDB. This makes saving and using tools much easier because we didn't have to look for our GDB each time. Then in ARCmap, in the same data frame we already have open and projected we use the Bearing Distance to Line tool located in the toolbox, Data Management, and Features to import the data as a layer showing the direction and distance from the four points of origin to each of the fifty points measured. In the tool we selected our excel file as the input, saved the output to our GDB and selected each of the appropriate headings for X, Y, distance and azimuth and clicked OK to run the tool. When it was finished we right clicked on the line symbol for the data layer and selected a good contrasting color for the symbol (sulfur yellow). While analyzing the data we were interested in the distance to each object. To add distance information about each of the lines we right clicked on the layer name and selected label features, this added the distance measure to each of the lines. Then we right clicked the layer name and selected properties then selected labels; first we selected label all features the same and selected the distance field, left the font size at 8, then we set the color of the labels to contrast with the background (figures 9,10)(tourmaline green). Because of the large number of lines in a small area it gets quite messy when viewed with labels at a smaller scale so we set the scale range to not show the labels beyond a scale of 1:1,000(figures 11,12).

Fig.9. The line data that was generated using the bearing distance
to line tool. The lines have been labeled with distances (meters).

Fig.10. The line data that was generated using the bearing distance
to line tool. Data is shown over base map layer.
The lines have been labeled with distances (meters).

Fig.11. Line and point data from survey 2 shown over a
base map layer scaled at 1:1000 with labels visible.

Fig.12. Line and point data from survey 2 shown over a
base map layer scaled at 1:1250 with no labels visible.

In order to display the points we gathered data on we used the Feature Vertices to Points tool located in Arctoolbox under Data management and Features. In the tool we selected the distance line layer as the input and saved the output in our GDB, we ran the tool. When the point’s layer appeared on the screen it was not very visible, so we right clicked on the point symbol and selected a good contrasting color (Tourmaline green). We were also interested in what the point was. To show this information we right clicked on the point layer and selected properties. In the properties tab we selected labels, we selected label all features the same, selected the name field for the labels and left the font size at 8. Again the density of the points with labels viewed at small scales gets messy so we set the labels to not show beyond a scale of 1:1,000. We selected a good contrasting color for the labels (Medium apple) and clicked OK to close. We noticed an issue with this tool; however, it also puts points on the origin ends of the lines and gives them a default label (figure 13). To remove these point and labels we opened the editor toolbar and selected start editing. Using the selector tool we selected each of the points at the origins and deleted them which automatically deleted the corresponding labels, we saved our edits and selected stop editing (figure 14). Now we were able to view the data we gathered layered over aerial imagery and analyze the data for accuracy and to see where our methods may need improvement (figure 15).

Fig.13. map of Randall Park with point and line layers, note the
points and labels at the origin vertices. 

Fig.14. The point data that was generated using the feature
vertices to points tool. The points have been labeled with the
object names.

Fig.15. Labeled points viewed over a base map layer of
Randall Park.

Discussion:

For the first portion of this project we measures a small set of objects and used a tree for our point of origin. This was more or less a practice run to become familiar with the equipment and to improve our methods. When we were gathering the X, Y data from the base map we found we had to be precise out as many significant digits as were available. When we first attempted to use abbreviated coordinates we found our plotted data about a half a mile south of where we gathered it from, by using all 6 decimal places we were able to get the data reasonably close to our study area. Another problem we ran into was using a tree as our point of origin. First, when gathering the data we rotated around the tree which progressively pushed our data off their marks. Second, when we tried to locate the exact point of the trunk it was obscured by the branches overhead so we had to use our best judgment of its placement.

During the second portion of our project we had to overcome the size of the study area, the best way to do that was to use multiple points of origin. The west points in the park were simple enough using the electric poles as our origins. To locate the base of these in the aerial image we found the pole but the base of it was difficult to see so we used the shadow of the pole to aid us. We used the point where the shadow ended or appeared to intersect the pole as our origin. Many of these points seem fairly accurate; however there were 2 points that were not. At the south-west corner we have one point that shoots off to the north-west at a considerable distance, this should have been a lamp located within the park (figure 16). There are several reasons that could have contributed to this including; the instrument could have had an error, the instrument may have been misread or the numbers may not have been communicated or written down accurately. The second point that is severely misaligned is at the north-west corner. There is a tree that should be within the confines of the sidewalk (figure 17). Again any of the same problems may have occurred and both of these points should be redone.

Fig.16. This image shows the incorrect line and point for a lamp
 post shot from the south-east corner of  Randall Park.

Fig.17. View of the north-west corner of Randall Park
and the incorrect line and point data for a tree.

On the east end of the park we used the rumble strips in the sidewalk as our origins. We carefully documented which corner of the strip was used at each corner of the park. These strips were easy enough to find in the aerial images; however, they were small enough and without shadows to corroborate their position it was difficult to get a precise reading on the corners. When we imported our data on this end of the park they are less accurate than the west end. I had commented that we should use the fire hydrants as our origins (figure 18). We decided against this because they were across the street and nearly covered in snow (figure 19). Doing this again, I would use the hydrants.

Fig.18. This fire hydrant would have made a better origin. Do to
its color and size it should have been easily recognizable in
aerial images.

Fig.19. This fire hydrant was located across the street from the
north-east corner of Randall Park. the rumble strip in the
foreground was used as the origin.

Comparing the tools used in the first part of this project to the second I believe they are equally accurate. The compass method takes more time to get precise azimuth readings while the True Pulse records both distance and azimuth at the same time; however it is not without fault. It seemed to me that it was more difficult to record data on a small object such as a lamp post at a distance with the True Pulse. The problem was holding the instrument steady long enough to get a reading. In a pinch it is quite feasible to accurately gather data with the more primitive methods. They may not fail when technology does.          

The process of adding labels to the layers in the map took a couple of extra minutes but it  gave us the ability to see the values associated with each of the points and lines. 

Conclusion:

This project allowed us to use methods that ranged from the more primitive to the more technological. Knowledge of each method is a great advantage if one method fails or another unforeseen circumstance arises. Instruments such as a compass and a tape measure do not have batteries which do not always like the environment they are being used in. Also, technology itself can simply fail without a fix in the field.

The group work is always a test in coordinating the schedules of the participants and working around each other’s prearranged activities and other priorities. This is a great skill to carry forward into the workplace as you may be coordinating projects with many people and organizations. 

This project was also an experience in dealing with changing weather conditions. Much of the week the weather was dry but cold, when we did our survey on Friday, 22 February 2013, we were dealing with several inches of new snow and light snow was falling (figure 20).

Fig.20. Several inches of new snow had fallen
before we did our survey. We did not have a ruler
with to measure the snow depth but this notebook is
about 5.25 inches to the top of the spirals.