Balloon Mapping Final Report

Introduction
Our geospatial fields methods class has been thinking conceptually about and working on an aerial mapping project of the University of Wisconsin - Eau Claire campus for a while.  Early on in the semester we did extensive research on the topic, and found that there was not a lot of information about it on the internet.  Therefore, we have been almost "winging it" and coming up with ideas on the procedure by ourselves.  Now that the weather has warmed up a little bit, we were able to finally put the project into action.

Methodology
Day 1:
We previously had constructed contraptions out of two-liter soda bottles to hold the camera in for the project, but those ideas have since been scrapped.  A small styrofoam container is now being used to house the camera for the project.  A hole was cut out of the bottom of the container for the camera to take pictures through.  The first task of the day was to inflate the balloon.  This was done by attaching a hose from a helium tank and inserting it into the opening of the balloon (Figure 1).

Figure 1. Helium tank/hose

Figure 2 shows the balloon as it was being inflated with helium.  The balloon was inflated until it had a diameter of about five and a half feet wide.

Figure 2. Inflating the balloon

After the balloon was inflated, zip ties were used to clamp the opening shut around a rubber ring.  Then, a carabiner was put on to the ring to attach it to the string that we would use to hold on to the balloon.  The string was measured and marked into 100 foot increments.  It was determined that the balloon was going to be let out 400 feet.  The styrofoam contraption housing the camera and a Garmin eTrex GPS unit were also attached (Figure 3).  

Figure 3. Attaching the camera contraption to the balloon

Continuous shot mode was turned on on the camera, and the shutter button was fastened down to continuously take pictures using rubber bands and tape.  Once everything was attached to the balloon, 400 feet of string was let out and the balloon mapping began.

Figure 4. Balloon being let out on the string

The class then began walking around campus, using care to guide the balloon through areas without getting the line snagged on trees or power lines.  This video shows the conclusion of the exercise.  We were just beginning to wind the string back in and bring the balloon down when something broke on the line due to severe tension caused by the heavy winds that were blowing on this day.  The balloon floated away and the container that had the camera inside of it fell into the river that flows through campus.  We were, however, able to retrieve the camera and get the pictures that were taken.    

The images that were taken were then to be mosaicked together to create one large aerial image of campus.   One method of mosaicking that I had no previous experience with and wanted to try was using http://mapknitter.org/.  This is a very user-friendly website for mosaicking.  The site provides aerial imagery, and the user simply loads images on top of that imagery.  The images are then dragged to their correct location, and can be resized, rotated, and distorted to combine the images together.
The map that I made using this site can be found here: http://mapknitter.org/map/view/uweccampus.

Day 2:
We decided to construct a different system for housing the camera for the second class of balloon mapping.  The winds during the previous class kept swinging the styrofoam container around, causing many images to be taken at oblique angles.  In order to make the more aerodynamic, the camera was attached to an arrow (Figure 5).  This would allow the wind to flow around the device, and hopefully reduce the amount of swinging around from side to side up in the air.

Figure 5. New device to hold the camera

The following videos document the process of inflating the balloon and attaching the camera to the string on the balloon.  This time, a metal ring instead of a rubber one was used to secure the various parts together.  

We were able to walk the balloon around and obtain imagery covering almost the entire campus.  The images were georeferenced and mosaicked together using ArcMap.  In order to save time, the campus was divided into six different sections.  Groups were then assigned to an area and were in charge of georeferencing images for that area.  Each group was then supposed to import a mosaic of their area into a geodatabase for a final mosaic of the entire campus.

Georeferencing is a relatively straight-forward process in ArcMap.  The first step is to obtain a reference image for the desired area.  The images that you want to georeference are then added to the document.  It is best to find images that are taken looking straight down towards the ground to limit the amount of distortion.  Enough images should be selected so that there is about a 60% overlap in the area covered by the image.  The georeferencing toolbar is then turned on and used to select the image that you want to georeference.  Using the add control points button, a point on the image is clicked, followed by clicking on the corresponding spot on the reference image.  Each image should have at least nine control points added to it to ensure an accurate georeference.   Figure 6 shows an image being georeferenced with its control points displayed.

Figure 6. Image with control points

Once all of the control points are added and the image is georeferenced properly, the image must be rectified.  This updates the georeferencing and saves the image as a new file.  Then, the next image is selected and the process is repeated until all of the images are georeferenced.  When all of the georefencing is done, the Mosaic to New Raster tool was used to mosaic the images together.  Figure 7 shows the final mosaic of the area that my group was assigned.

Figure 7. Mosaic

One issue that arose during the geoferencing process was the string being visible in some of the images.  I tried choosing images where the overlap would remove the string, but it is still visible in two of the images in the mosaic.

Figure 8. Mosaic of Entire Campus

Discussion
We were able to take away quite a bit of knowledge from the first day of balloon mapping.  It was a very windy day, which influenced the quality of images we got, and ultimately led to the loss of the balloon.  Therefore, the weather conditions must be considered for a project like this.  A sunny day with calm or gentle winds would be ideal.  When the balloon was up in the air, the wind tossed around the styrofoam box that contained the camera.  This led to the camera taking many pictures at odd angles.  Those images were distorted, and not useful at all for creating a mosaic.  Because of that issue, we decided to create a new contraption for housing the camera for the second day of balloon mapping utilizing an arrow.  This was much more aerodynamic, and we were able to get better pictures facing straight down.  The high winds also affected the flight of the balloon.  Rather than rising straight up, the balloon was pushed way off to the side (Figure 4).  This severely shortened the elevation of the balloon up in the air and limited the expanse of coverage of the images taken by the camera.    

Due to recent construction on campus, there are no reference images that are up to date.  This made the georeferencing of some areas very difficult.  A few members of the class attempted to take ground control points using various GPS units.  There was a discrepancy in the location of points among the various units so I chose not to use the points during the georeferencing process.

Conclusion
The two balloon mapping sessions turned out to be very successful, despite losing the balloon on the first launch.  We were able to get many good images of campus to georeference and mosaic together.  The first class of balloon mapping also provided us with a lot of information to make the second attempt much better.  We learned what effect the weather could have on a project like this, and created a better device to hold the camera for the second launch.  In addition to using ArcMap to georeference and mosaic the images, I was also introduced to Map Knitter, which is a website where you can add images together on top of an aerial image.

Balloon Mapping

Introduction
Our class is embarking on an aerial mapping project of our college campus.  A large helium balloon was used with a camera attached facing downwards.  A long string was then tied to the balloon so we could move the balloon around campus, as well as set the desired altitude of the balloon.     

Methodology
The imagery was gethered using a large balloon that was launched into the air about 400 feet.  Attached to the balloon was a camera facing downwards.  Once the balloon was at the desired altitude, we walked all around campus to collect as much imagery as possible.  After this process was completed, the images from the camera were located onto the computer.  Relevant images pertaining to the assigned area were selected and were georeferenced.  Georeferencing is accomplished by adding control points to the image and matching them to the corresponding location on another image that is already georeferenced.  The first step in this process is to display an already georeferenced image, followed by turning the georeferencing toolbar on.  An image that needs to be georeferenced is then loaded, and fit to the display. 

Figure 1. Aerial image to be georefenced displayed.

Using the add control points tool, a control point is clicked on the image, and then again on the corresponding location on the already georeferenced image.  These control points can consist of the corners of buildings or sidewalks, trees, or any other distinctive featuers.  This process is repeated until the image appears to be in the correct location.  When georeferencing my images, I tried to have at least 10 points.

Figure 2. Aerial image with control points displayed.

Once done georeferencing an image, it must be rectified to be saved as a new file.  Then, other images are added to the display and georeferenced until the desired area is covered by the newly georeferenced images.

Figure 3. Additional images being added and georeferenced.

When all of the desired images are georeferenced, the mosaic to new raster tool is employed to combine the images into one file.

Conclusion
Figure 4 shows the final mosaic of the images that I georeferenced. 


Figure 4. Final mosaic of imagery.

Final Navigation Report

Introduction
Over the past few weeks, our Geospatial Fields Methods class has been participating in different land navigation techniques.  This process began by spending the first week establishing pace counts for each person in the class and creating maps that would be used for navigation with a compass.  The next week, we were put into groups and assigned six points that we were to navigate to using traditional map and compass navigation.  The next field outing consisted of navigation to a different set of six points using just a Garmin eTrex GPS unit.  The field outings concluded this past week with a final navigation activity that incorporated paintballing.  Each group was to navigate to as many points possible with the use of a GPS unit and maps that were created.

Study Area
Our field navigation exercises took place on the lands surrounding The Priory, which is located just to the south of the city of Eau Claire.  An aerial image of the area, navigation points, and 5-meter contours can be seen in Map 1.  

Map 1. Study Area

The aerial image shows that the study area is mostly wooded with a few distinct features that aided in the navigation.  These included the highway and waste pond bordering the area to the north, the planted pine tree region to the east, and the ridge stretching through the area as evidenced by the contours.  

Methodology
Week 1
In preparation for the first week's field outing, we needed to establish our pace count and create the navigation maps that we were to use out in the field.  Our pace count was established by marking off a distance of 100 meters and counting the number of paces it took us to walk it.  I found my pace count to be 65.  To create the navigation maps, data such as a orthophotograph, two-foot contour lines, five-foot contour lines, and a DEM was used.  A UTM grid was also placed over the map to aid in the navigation.  Each group member created two maps for the event and then as a group, two final maps were selected to use in the exercise (Maps 2 and 3).

Map 2. My map for traditional land navigation exercise.

Map 3. Hannah's map for traditional land navigation exercise

Week 2
On the day of the field event, we plotted the locations of the points that our group was assigned to navigate to.  Straight lines were then drawn from point to point, and a compass was used to measure the bearing.  

Figure 1. Mitch and Hannah plotting points. 

We then went out in the field and began our navigation event.  Our group utilized a three-person system for the exercise.  One person had the compass and would direct a person to walk to a specified location on the bearing.  The final person would then walk to that person and count the number of paces to estimate the distance traveled.  This process was repeated until our navigation points were located. 

Figure 2. Mitch standing at point marker and directing Hannah towards next location.

Week 3
The next week, we were to use GPS units to navigate to the points rather than using the traditional land navigation techniques using a map and compass.  Each student was assigned a Garmin eTrex GPS unit for the activity.  The unit would be used to locate the navigation points that we were assigned and to track the routes that were taken while navigating to the points.  My group was assigned the points on Course 3, with point 1B being our starting point and heading to the other points in order.  

Table 1. Navigation Points

My group utilized the UTM coordinates to navigate to the points.  To get to the points, we generally began by navigating to the correct x value, and then walked to arrive at the correct y value.  A recent snowstorm made walking slow and a bit difficult.

Figure 3.  Hannah and I examining our GPS units at a point marker.

After we navigated to all of the points, we returned to the parking lot where the class was congregating and turned off the tracking on the GPS units.  This data was then uploaded as a shapefile using the Minnesota DNR Garmin Application.  The shapefile was uploaded in the NAD 1983 UTM Zone 15N projection to be consistent with the other files that were used for mapping of the priory area.  Each student's track log was then imported into a feature dataset which allowed for access of all of the files for everyone.  This data was then used to create maps displaying the track log from my GPS unit, the track logs for my group, and a map containing the track logs of everyone in the class.

Week 4
The final activity incorporated paintballing into the navigation exercise.  Each group was to navigate to as many of the 18 navigation points as possible using a Garmin eTrex GPS unit and maps that we created for the event (Maps 5 and 6).  

Map 5. Paintball navigation exercise map. 

Map 6. Paintball navigation exercise map.

The maps were to aid the GPS units in the navigation to compare the ease of navigation to the previous week in which we only had GPS units.  The track logs were again turned on to track the locations of each person, and waypoints were to be taken at each of the point markers.  The rules for the paintball aspect was that if a person was shot, their group had to sit still for two minutes and not shoot at anyone.  We were also given the option of wearing snow shoes because of the high depth of snow still on the ground.  The activity began with a few minutes of non-shooting time while each of the six groups spread out to where they wanted to begin.  After the exercise, the waypoints and track logs were imported using the Minnesota DNR Garmin Application, and maps displaying my track log, my other group member's track log, and the track logs for everyone in the class were created.
  
Discussion
Overall, the different navigation events went very well for our group.  In the first activity using a map and compass, we were able to utilize a method that allowed us to move to the points quickly and efficiently.  However, there were a couple minor issues that we had to overcome.  The pace count that we established was done in a flat parking lot, and was not very conducive to estimating accurate distances when walking through the woods.  There were many hills that we had to walk up and down, as well as many trees and other obstacles that made walking in a straight line difficult.  When walking between points four and five, we came across some ponds that were fenced off.  In order to accurately maneuver around them, we counted a number of paces to the side of them.  Once we were around the ponds, those same number of paces were walked sideways to get back on the correct bearing. As mentioned earlier, we also the grid issue on Hannah's map that did not allow us to plot the UTM points.  Experiencing this shortcoming has stressed the importance of reviewing every detail before going out in the field.   

The maps that we prepared were great resources in the field.  The aerial imagery was very helpful in determining what type of terrain we were in and should be going to.  The DEM symbology and contours were also useful for tracking our progress on the map.  We had to walk up and down a few hills, and this information allowed us to make an accurate estimate of our location in terms of the points we were navigating to.  The point data we were given had the elevation in meters listed, and Map 2 that I created was useful because the five-foot contours were labeled.  For future navigation exercises, I would create maps very similar to the ones that we created for this event because the information we included on them was very helpful in the field.  One change would be to include the grid on both maps.  

After the completion of the second field outing, it was apparent that navigation with a GPS is easier and faster than traditional navigation with a map and compass.  GPS navigation does not require any preparation time, and it is much quicker in the field because a person can continuously walk and not have to worry about walking to a certain spot on the bearing and count the number of paces.  It also can be accomplished easily by oneself, whereas in the traditional method, a three person group is ideal.  Another advantage of GPS navigation is that a waypoint can be created on the GPS and it will tell you which direction and how far to travel to this location.  We did not do this during our navigation exercise, but this would have been very helpful and effective to do.   

Even with these benefits of GPS navigation, we did run into a few minor issues in the field.  It was very easy to misread some numbers when walking and looking at the GPS which led us a little out of our way a couple times.  An example of this can be seen in the animation of my track (http://www.youtube.com/watch?v=iP7FNiIi3xk) between points 3, 4, and 5.  When using UTM coordinates, it is important to remember that the x values increase as you move to the east, and y values increase as you move to the north.  A map accompanying the GPS unit can be very helpful to visualize this when determining the direction to travel.  This led us to the final navigation exercise where we had a map to accompany the GPS.  This method proved to the the quickest and most efficient method of land navigation.  Maps 7-12 display the track log data from each of the two navigation exercises where GPS units were used.  

Map 7. My track log from GPS navigation exercise.

Map 8. My track log from GPS and map navigation exercise. A green to red color ramp was used to symbolize the time.

Map 9. My group's track logs from GPS navigation exercise.

Map 10. My group's track logs from GPS and map navigation exercise.

Map 11. Class track logs from GPS navigation exercise.  I was assigned to Group 3.

Map 12. Class track logs from GPS and map navigation exercise.  I was assigned to Group 3.

When comparing the tracks from these two exercises, it is evident that the tracks taken between points are much more direct in the second exercise when we were allowed to have a map.  This is also apparent when the time data from the track logs is examined.  In the first GPS exercise, my group traveled to five points (not counting the starting point) in 1 hour and 18 minutes.  In contrast, my group traveled to 14 points in 2 hours and 28 minutes during the second exercise.  This also includes time that was spent engaging in fire with other groups.  The map was a great reference to use during the navigation, and eliminated time spent walking in the wrong, or not always most direct line to a point as seen in Map 7.  We were able to use the map to determine an efficient route in terms of the order the points would be navigated to.  Physical features such as the type of land cover and ridges that were evident from the map were also great references for the location of each point.  One trick that our group did not take advantage of, and would have helped immensely, was to use the coordinates of the navigation points and create waypoints in our GPS unit.  The GPS would then be able to give us the direction and distance we needed to travel to that point.  

Conclusion
These field navigation exercises provided an excellent understanding of three different navigation methods: traditional navigation with a map and compass, GPS navigation, and GPS navigation with the aid of a map.  My group was able to successfully navigate to points using these methods, and upon reflecting on them, decide which method was the easiest and most efficient.  This turned out to be navigation with a GPS and map.  Navigation with just a GPS unit is not a bad option, but having a map available all the time is not very conceivable.  Finally, the method of navigation with a map and compass was the slowest, but is still an effective option in cases where GPS technology is failing the user.

GPS Navigation

Introduction
Over the past few weeks, our Geospatial Fields Methods class has been exploring different land navigation techniques at The Priory.  First, the traditional technique of using a map and compass was used to navigate to six different point markers in a wooded area.  This week a Garmin eTrex GPS unit was used to navigate to six different points.  The GPS units had the tracking feature on, which was used to create maps and an animation showing the routes of students through the woods.  Next week we will be participating in a paintball activity that involves navigating to as many points as possible.  

Methodology
In preparation for last week's field outing, we needed to establish our pace count and create the navigation maps that we were to use out in the field.  Our pace count was established by marking off a distance of 100 meters and counting the number of paces it took us to walk it.  I found my pace count to be 65.  To create the navigation maps, data such as a orthophotograph, two-foot contour lines, five-foot contour lines, and a DEM was used.  A UTM grid was also placed over the map to aid in the navigation.  On the day of the field event, we plotted the locations of the points that our group was assigned to navigate to.  Straight lines were then drawn from point to point, and a compass was used to measure the bearing.  We then went out in the field and began our navigation event.  Our group utilized a three-person system for the exercise.  One person had the compass and would direct a person to walk to a specified location on the bearing.  The final person would then walk to that person and count the number of paces to estimate the distance traveled.    

This week, we were to use GPS units to navigate to the points rather than using the traditional land navigation techniques using a map and compass.  Each student was assigned a Garmin eTrex GPS unit for the activity.  The unit would be used to locate the navigation points that we were assigned and to track the routes that were taken while navigating to the points.  My group was assigned the points on course 3, and started at point 1B and then went to point 2B.  The other group that was assigned to course 3 started at point 1B and went to point 6B.

Table 1. Navigation Points

My group utilized the UTM coordinates to navigate to the points.  To get to the points, we generally began by navigating to the correct x value, and then walked to arrive at the correct y value.  A recent snowstorm made walking slow and a bit difficult.

Figure 1. Hannah and I examining our GPS units at a point marker.

After we navigated to all of the points, we returned to the parking lot where the class was congregating and turned off the tracking on the GPS units.  This data was then uploaded as a shapefile using the Minnesota DNR Garmin Application.  The shapefile was uploaded in the NAD 1983 UTM Zone 15N projection to be consistent with the other files that were used for mapping of the priory area.  Each student's track log was then imported into a feature dataset which allowed for access of all of the files for everyone.  This data was then used to create maps displaying the track log from my GPS unit, the track logs for my group, and a map containing the track logs of everyone in the class.

Map 1. Track log from my GPS unit.

This map shows the route that I took during the field navigation event.  Symbology was used to display the beginning of the track in a lighter color.  The color then gradually becomes darker as the track progresses.  This data was then used to create an animation of the track.  To do so, the file was selected as a time track under the properties.  The animation toolbar was then used to create and export the video.  The video can be found here: http://www.youtube.com/watch?v=iP7FNiIi3xk.  The files from the rest of the students in the class were added into ArcMap and maps were created to show their track logs.

Map 2. Group GPS Navigation Map

This map displays the track logs for Hannah and me.  Mitch's file was not in the file when it was accessed.  As you can see, Hannah's track log had much fewer points, and is most likely due to a difference in the increments that the GPS unit took points.  

Map 3. Class track logs.

Discussion

After the completion of this field outing, it was apparent that navigation with a GPS is easier and faster than traditional navigation with a map and compass.  GPS navigation does not require any preparation time, and it is much quicker in the field because a person can continuously walk and not have to worry about walking to a certain spot on the bearing and count the number of paces.  It also can be accomplished easily by oneself, whereas in the traditional method, a three person group is ideal.  Another advantage of GPS navigation is that a waypoint can be created on the GPS and it will tell you which direction and how far to travel to this location.  We did not do this during our navigation exercise, but this would have been very helpful and effective to do.   

Even with this benefits of GPS navigation, we did run into a few minor issues in the field.  It was very easy to misread some numbers when walking and looking at the GPS which led us a little out of our way a couple times.  An example of this can be seen in the video of my track between points 3, 4, and 5.  When using UTM coordinates, it is important to remember that the x values increase as you move to the east, and y values increase as you move to the north.  A map accompanying the GPS unit can be very helpful to visualize this when determining the direction to travel.  Finally, GPS technology can not always be relied upon so it is important to have an understanding of traditional navigation techniques.  The batteries in the unit could die, or you could be in an area where it is difficult to obtain a reliable signal.      

Navigation with a Map and Compass

Introduction
The objective for this week's exercise was to navigate through the woods to a series of points using a map and a compass.  This exercise is the follow-up activity to last week's prep work, consisting of the creation of maps and the establishment of each person's pace count.  

Methodology
The preparations for this week's field activity took place last week with the establishment of a pace count and creation of maps of the area of interest.  To establish each student's pace count, 100 meters was marked off in a parking lot.  We then walked the distance and counted the number of paces it took.  I walked the distance three times, and had a consensus pace count of 65.  Maps were then created of the area of land around the Priory using a variety of data sets (Maps 1 and 2).

Map 1. Priory Navigation Map with DEM and Two-Foot Contours

Map 2. Priory Navigation Map with Orthophoto and FiveMeter Contours

As a group, we chose to use Hannah's map in our navigation exercise (Map 3), as well as Map 2.

Map 3. Hannah's Navigation Map

 The field event took place the following week on March 4th.  A snowstorm was moving into the area, but there were only a few flurries during the exercise.  As previously mentioned, our goal was to navigate to five different points using a compass and the maps that we had created.  The first step in the process was to plot the points on our maps using the UTM coordinates that were given to us.  In attempting to do so, it was evident that the grid that Hannah put on her map was not correct.  This put our group in a quandary because there was no way for us to plot the points.  Luckily, we were able to use another group's map.  After the points were plotted on the new map that was given to us, a straight edge was used to draw lines connecting each of the points.  These lines were used to calculate the bearing.  To do so, the compass was placed on top of the map facing the direction that we wanted to travel.  The dial on the compass was then turned so the lines were facing straight up to the top of the map.  This process was completed for each of the five points on the course we were given.

Image 1. Mitch and Hannah Plotting Points

The scale on the map was then used to draw an estimate for the distance between each of the points.  This would prove to be very useful in the field because we could use our pace count to estimate how much further we would have to navigate.

Map 4. Approximate Location of Navigation Points

After our points were plotted, and the bearing and distances were calculated, we set outside to begin our navigation.  We went to our starting point and were to navigate to the designated points where there was an orange marker and a paper punch to show that we made it to each point.  Our method of navigation began with Mitch using the compass and dialing the bearing that we had calculated earlier.  He would then have Hannah walk to a spot (usually a specific tree) on that bearing.  I would then walk in a straight line to Hannah and count the number of paces to provide us with an estimated distance traveled.  We continued this process until our destination was reached.  Image 2 and 3 depict Mitch standing next to the first marker and directing Hannah to a tree on the bearing to our second point.

Image 2. Point Marker 

Image 3. Hannah Walking to a Tree

Discussion
Overall, the navigation event went very well for our group, as we were able to utilize a method that allowed us to move to the points quickly and efficiently.  However, there were a couple minor issues that we had to overcome.  The pace count that we established was done in a flat parking lot, and was not very conducive to estimating accurate distances when walking through the woods.  There were many hills that we had to walk up and down, as well as many trees and other obstacles that made walking in a straight line difficult.  When walking between points four and five, we came across some ponds that were fenced off.  In order to accurately maneuver around them, we counted a number of paces to the side of them.  Once we were around the ponds, those same number of paces were walked sideways to get back on the correct bearing. As mentioned earlier, we also the grid issue on Hannah's map that did not allow us to plot the UTM points.  Experiencing this shortcoming has stressed the importance of reviewing every detail before going out in the field.  

The maps that we prepared were great resources in the field.  The aerial imagery was very helpful in determining what type of terrain we were in and should be going to.  The DEM symbology and contours were also useful for tracking our progress on the map.  We had to walk up and down a few hills, and this information allowed us to make an accurate estimate of our location in terms of the points we were navigating to.  The point data we were given had the elevation in meters listed, and Map 2 that I created was useful because the five-foot contours were labeled.  For future navigation exercises, I would create maps very similar to the ones that we created for this event because the information we included on them was very helpful in the field.  One change would be to include the grid on both maps.  When making a map, it is important to have all of the data layers in the same coordinate system to insure accuracy.  Finally, making sure the correct grid is used is essential.

Conclusion
The navigation event conducted at the Priory went very well for me and my group.  Once the points were plotted on maps that were created, a compass was used to calculate the bearing in which to walk to successfully locate the next point.  Distances were also estimated and related to pace counts that had been previously established to approximate how much further we needed to travel to find the point.  We were able to effectively navigate to the points via teamwork and the information that was included on the maps.   The one main issue we encountered was the inaccurate grid that did not allow us to plot the points on the maps that we had.  This was an example of learning the hard way that all details and information should be carefully evaluated to ensure the greatest possibility of success in any line of work.

Field Navigation Part One

Introduction
This weeks assignment consisted of preparation for a field navigation exercise that will take place at the Priory.  This land, purchased by the university to be a day care facility, is located to the south of the city of Eau Claire.  The image below shows that the land that we will be navigating through is mostly wooded.

Image 1. Area of Interest

 

The activity will consist of a series of points that we will need to navigate to using a compass and maps that we created.  We will not be using a GPS, as the purpose of the exercise is to learn to navigate without the aid of technology.  Since this area is mostly wooded, a GPS might not be very accurate anyways.

Methodology
The first step in our preparations involved establishing every person's pace count, which is the number of steps taken in a given distance.  This will be useful for our navigation because we will not have a GPS available, and we can use our pace count to tell how long of a distance we are walking.  A laser rangefinder was used to find a distance of 100 meters in a parking lot, and the end points were marked with snow.  Each person in the class then walked the distance, keeping track of the number of normal paces that they took.  After walking the distance three times, I found my pace count to be 65.  It should be noted that this was done on a sidewalk, and that a pace count might differ when walking through the woods and avoiding obstacles.

After the pace counts were established, our next task was to create the maps that we would use in our navigation exercise.  There was a suite of data sets available, but it was up to us to determine what would be useful to have on a our maps.  The data available consisted of: a topographic map of the region, color and black and white orthoimages, two foot contour intervals, five meter contour intervals, shapefiles of the area of interest, and a DEM.

When working in GIS, it is extremely important to be aware of coordinate systems.  ArcMap uses on the fly projections to project data that are in different coordinate systems.  This is nice for displaying data as you are using it, but any analysis should be done with data in the same coordinate system.  It should be noted that it is best practice to work with files in the same coordinate system to prevent errors and inaccuracies.  There are many different coordinate systems, and the appropriate one should be chosen to work best with the area of interest.  The area of interest for this project is very small, so a state plane or UTM coordinate system is ideal.  The UTM 15 North coordinate system was selected.  This coordinate system will work well because we can create a UTM grid and overlay that on top of our maps to aid in the navigation.

During the beginning of map construction, the two foot contour data was giving us problems.  This file was converted from a CAD data set, and did not have a projection.  When it was added to the other layers in ArcMap, it was not displayed.  To solve this problem, a blank document was opened, and the two foot contours were the first file added.  After this, the other data layers were added in the UTM 15 North projection.  I decided to make two maps for this navigation exercise.  The first consisted of the DEM, two foot contours, and a UTM grid.  The DEM covered a much larger spatial extent than our area of interest, so the Extract by Mask tool was used to extract the area of interest from the final file.  This smaller area had a smaller range of values, which made for better symbolization.

Map 1. Navigation Map with DEM and Two Foot Contours

The second map was to have a much more simple design.  For this, the orthophoto was used as the base, and the area of interest and five meter contours were overlaid.

Map 2. Navigation Map with Orthophoto and Five Meter Contours

    Each person in our three person group created their own maps, and then as a group we were to collaborate and choose two maps that we liked best for our navigation.  My second map of the orthophoto and five meter contours was chosen, as well as Hannah Bristol's map pictured here.

Map 3.  Hannah's Navigation Map

Discussion
This weeks assignment was based on preparations, and a more detailed account of the exercise will come next week after we actually partake in the activity.  The preparatory work did have value in terms of establishing a pace count and discussing how it can be used for navigation, as well as stressing the importance of knowing and understanding coordinate systems.  When working with different data sets, they should always be in the same coordinate system.  If not, the project tool should be used to convert them.  Also, the appropriate coordinate system should be used, depending on the extent of the area of interest.  For a small region like this, the UTM Zone 15 North works very well.  A state plane coordinate system could also be used, but one must be aware of the extent of the zones, because you do not want the area of interest to overlap into two or more zones.  Finally, map elements were an important aspect of this exercise.  We were to determine which files we wanted to have on our maps without them being too cluttered.  Scales, north arrows, grids, and the sources of data also had to be included.

Distance and Azimuth Survey

Introduction
The objective for this lab was to conduct a survey of point data in a quarter hectare using the distance and azimuth from a given origin.  Mitch Collins was assigned to be my partner for this project.  The point data could be collected in two different ways: using a range finder for the distance and a compass for the azimuth, or using a more high-tech TruPulse laser range finder that measures both.  This project was conducted in two parts.  The first was during class on February 18th, where the procedure, concepts, and equipment was introduced.  The final data collection occurred on February 24th with my partner.  In class, the concept of magnetic declination was discussed.  Magnetic declination is the angle between magnetic north (direction in which a compass points) and true north (direction in which the north pole is located along the Earth's axis).  Magnetic declination varies depending on the location on Earth, as well as over time.  It is important to be aware of and adjust for it because it affects navigation.  Here is a link to a webpage on the National Oceanic and Atmospheric Administration's website that calculates the magnetic declination based on location.
http://www.ngdc.noaa.gov/geomagmodels/Declination.jsp
The zip code for Eau Claire, WI was put in, and it was found that the city has a declination of 0° 58' W.  This is a very small declination, and means that magnetic north lies  0° 58' counter-clockwis of true north.  

Methodology
As mentioned before, the first part of this lab activity took place in the classroom, where the concepts and equipment were introduced.  After this, the class went outside behind Phillips Hall and practiced using the equipment to obtain the distance and azimuth of objects.  The location of this practice can be seen in Map 1. As you can see, this area is located between Phillips Hall and the parking lot.  In this area, the TruPulse laser rangefinder and a compass and sonic rangefinder were used to take points of objects such as trees, signs, and sculptures.  The tree near the corner of the building was designated as the origin.  The origin can be found using a GPS device, or by using a recognizable feature that can be found on a high resolution aerial image.

Map 1. Practice Run with Equipment for Distance and Azimuth Survey

The sonic rangefinders require two people for operation.  One person takes a unit and stands with it at the desired point and faces the other person with the receiver.  The person with the receiver then is able to find the distance between these two points.  They then must use a compass to find the azimuth.  The TruPulse laser rangefinders make this process much easier, as they can calculate many variables using different measurement modes.  In this lab, the azimuth, as well as the slope distance were the only relevant measurements.  The slope distance is the straight line distance between the TruPulse and the target object.  Although it was not used in this lab, the TruPulses also have a feature where data can be transferred via Bluetooth for mapping.

During this trial, each group got a turn using the equipment, and recorded the distance and azimuth for a few points.  This data was then stored in an Excel file brought into ArcMap.  Two tools were then used to transform the tabular data into points on a map that correctly model a position.  The first is Bearing Distance to Line, located under Data Management Features-->Features.  This tool creates a line representing the distance and azimuth from the origin.  When attempting to use this tool, many people in the class were having troubles.  Help menus were searched, and by trial and error, a solution was found.  The first step in this process is to create a geodatabase.  The Excel file must then be imported into that geodatabase.  To ensure accuracy, the cells containing the coordinates for the origin were formatted to show all of the decimal places.  After the Excel file was imported into the geodatabase, the Bearing Distance to Line tool was able to be used successfully. The final tool to be used was Feature Vertices to Points, also located under Data Management Features-->Features.  This tool placed a point at the end of each vertices that was created using the Bearing Distance to Line tool.  
On our actual survey day, Mitch and I chose to do an area at the edge of the Hibbard parking lot along State Street.

Map 2. Locator Map of Study Area of Parking Lot along State Street

    We chose a "No Parking" sign that was located at the end of a row of parking spaces as our origin.

Image 1. Location of Origin

 The TruPulse laser rangefinder was then used to measure the slope distance and azimuth of 50 points.  These points consisted of trees, bushes, stop lights, street signs, fire hydrants, and the front doors of houses.  

Image 2. View of State Street and Edge of Parking Lot from Origin

After the collection of the point data, an Excel file was created, and then brought into ArcMap.  This table can be seen in Table 1.  The table contains fields for the point number, X and Y coordinates for the origin, distance, azimuth, and point name.  An aerial image was loaded to find the coordinates for our origin.  

Table 1. Distance and Azimuth Data

The table was imported into a geodatabase that was created for this lab, and the Bearing Distance to Line tool was used.

Map 3. Results of the Bearing Distance to Line Tool

Map 3 depicts the line segments that were created representing the distance from the origin to the points.  The Feature Vertices to Points tool was then used to create points at the end of the line segments (Map 4).

Map 4. Results of the Feature Vertices to Points Tool 

A final map was then created to show the point locations of the objects where the distance and azimuth was measured.

Map 5. Final Map showing Point Data

Discussion
Our study area consisted of the end of the Hibbard parking lot, as well as the nearby areas along State Street and Garfield Avenue.  Our points consisted mainly of bare trees, bushing extending up from the snow, and street signs.  We also measured the slope distance and azimuth to the stop lights surrounding the intersection.  After examining Map 5, it was noticed that some of the points on the aerial image did not match up with the objects in real life.  Most of these points are located in the middle of State Street, which runs north to south on the map.  We did not take any points in the street, as most of the points were of trees or signs that were located along both sides of the street.  These points appear to be between five and ten meters away from their expected locations.  This might be attributed to the laser moving past a sign, tree, or bush and instead measuring the distance to a given spot on the road.  An error in the recording and entry of data could also attribute to this problem.  The point that is furthest north on the map certainly appears to be an outlier.  There also is the chance that the aerial image is slightly distorted and is the cause for some of the anomalies.       

The evolution of technology can be seen when examining the equipment that could be used to conduct a survey of points.  The first method described involves using sonic rangefinders and a compass.  This would require a second person to move to the desired points to collect the data.  It would not be a very fast and efficient method if only one person was sent to survey the area.  Another issue could be the precision with which the azimuth is measured using a compass.  Using the TruPulse was a much faster and easier method of conducting the survey.  It quickly switches between measurements modes to make a wide variety of measurements.  It also has Bluetooth to transfer data.  One of the downsides of a TruPulse is its expensive price.  These two methods have been in large part, become outdated by GPS technology.  GPS units allow a person to quickly move between objects and capture points.  These can then be easily transferred to a computer for analysis.  One of the negatives associated with using GPS is the idea that technology can fail a person at any time.  There could be software and equipment issues, or loss of power, making the understanding of low-tech methods of surveying important when in a bind.  GPS surveying is also not always an option due to location and topography.  An accurate signal is not always attainable near tall buildings or under tree cover.  Therefore, the use of a TruPulse laser rangefinder would be ideal for surveying objects in a forest or another area where a GPS signal is unreliable.

Conclusion
This lab was a great experience to see how surveying point data could be accomplished without the use of GPS technology.  This process has evolved from using sonic rangefinders and a compass to a laser rangefinder that has many different measurement modes.  Although using GPS would be the easiest way to survey an area, it can not always be trusted.  During the process of loading the data that we collected into ArcMap, we encountered some problems with getting the Bearing Distance to Line tool to work.  Through the consultation of online resources, as well as the collaboration of other students, we were able to work through this issue and display our results.  Finally, we were able to display the points that were derived from the distance and azimuth data that we measured on top of an aerial image.  This allowed us to compare our data points to the features that are visible in the image.  This showed good results for the most part, although it does appear that nine of the 50 points are incorrectly located in the street.