Lab 12: Development of a Field Navigation Map

Introduction

            Having already learned how to use GPS units for navigation exercises as outlined by the blog posts below, the purpose of this lab was to expand our GPS skill set to include database design and creation for deployment in the field to a handheld GPS unit. Outlined by this blog post will be the methods involved in how to prepare for specific data collection in the field in regard to the database structure deployed to the GPS unit prior to the gathering data. Specifically, information for restoring the recreational features at the Priory owned by UW- Eau Claire would be gathered.

Methods/ Discussion

            The first step in creating the database that would be used to map these recreational features was to brainstorm a list of possible topics that could be easily mapped at the Priory. The list compiled included: trails, benches, erosion points, notable view points, large/ notable trees, woodpecker holes, human objects (garbage, dumps, fence, deer stands, trail markers, etc.), animal tracks, and bird houses. Next delegation of these topics to the three person teams the class was divided up into took place so teams were only responsible to map a specific feature at the Priory.

            My team consisting of Tonya O. and Chuck P. were assigned the trails of the Priory and decided to map all trails to include several attributes. The attributes to be mapped were trail surface, trail condition, and trail use. To aide in data collection and to standardize all recorded attributes, domains were created. The purpose of domains is to finalize what specific attributes can be recorded because a list of specific options (domains) will display once an attribute is selected on the GPS unit. For all of our domains, we used the text setting to record data type. In addition to selecting text as the data type, other domain coded values include float, short and long integer, raster and other types to allow for specific data types to be defined. Some benefits of using well defined domains are they expedite data collection because it allows the user to pick the domain from a drop down list instead having to type them in each time, and it prevents spelling errors that would affect our ability to manipulate and sort the data when post processing.

Figure 1: Trimble Juno GPS unit used for data collection at the Priory

Figure 2: Data structure within Trails trails feature class for deployment to the Trimble  Juno GPS unit for data collection at the Priory.

            After the domains were set for each attribute in the trails feature class, the geodatabase it was contained in was brought into a session of ArcMap to prepare it for deployment by changing the symology of the features to pertain to the data being gathered. In addition to changing the symbology of the feature class to line, a raster clipped down to just show the Priory would be included to help facilitate data collection by providing a basemap to reference. Next, using the ArcPad Data Manager Extension within ArcMap, the geodatabase layers we created were deployed using the “Checkout Wizard” function. Once the map was turned into a file type (.apm) that the Trimble GPS could recognize, simply copying and then pasting this folder onto the SD card on the GPS was all that was necessary to finish deploying the database to the unit. Once deployed, simply opening the file within ArcPad on the GPS was all that was necessary to begin data collection. Instead of having the GPS unit automatically and continuously drop vertex points as we walked along the trail, we decided to manually plot the points periodically along the trail to follow its path in addition to assigning the coded text domain values. Following collection of the attributes for the trails feature class, we then uploaded the line feature collected back into a session of ArcMap to be displayed.

Figure 3: Trail condition map of the Priory 

Figure 4: Trail surface map of the Priory

Figure 5: Trail use map of the Priory

Conclusion

            Although our class was unable to compile a complete map of all of the proposed topics at the Priory, we were able to gain many valuable skills regarding database creation for deployment in the field. In addition to those skills, we also had to trouble shoot problems as they arose due to the fact that many of us had never created a database like this from the ground up before which is in my mind, a very effective method to teach this. In conclusion, I found this lab extremely valuable because it allowed us to come up with the domain types on our own to show us how important it is to put thought into database creation prior to deployment in the field so you know specifically what it is that is being collected. 

Lab 11: High Altitude Balloon Launch

Introduction

            Outlined by this blog post will be the launch portion of our High Altitude Balloon Launch (HABL) project from the University of Wisconsin- Eau Claire Campus to supplement the post outlining rig construction. After refining and finalizing the design of the HABL rig, it was then time to play a waiting game with Mother Nature to allow for suitable launch conditions. The final rig consisted of an upside down Styrofoam box securely sealed with packaging tape that had a hole cut in the bottom that would allow the Flip camera housed inside to have an unobstructed downward view toward earth, a GPS beacon that would be used recover it, and hand warmers to prevent the electronic equipment inside from freezing at altitude. Connecting the rig to the base of the balloon was the parachute that would safely return the camera back to earth once the balloon reached its service altitude and popped due the change in air pressure.

Launch

On April 26, 2013, Dr. J. Hupy and the rest of the Geog 336 class launched a digital camera attached to an eight foot diameter, helium filled weather balloon to a height of nearly 100,000 feet above the earth’s surface. Conditions were not perfect, but due to the end of the semester quickly approaching, we had to make do with what was presented to us. There was a slight wind (10-15mph) from the west, with clear skies. Shortly after the launch, the balloon began its eastward flight path, and was quickly out of sight due to its high rate of accent. Following the relatively uneventful launch, we then went inside to begin tracking its flight using the GPS tracker placed within the rig. Nearly an hour passed before it transmitted its first location and then a little while longer before finally landing just outside of Marshfield, WI, over 78 miles away from where it was launched. Ultimately coming to rest at the top of a fifty foot tree, Dr. Hupy first obtained permission from the landowner to look for the HABL rig before having to climb up the tree himself to finally retrieve the undamaged and still intact HABL rig..

Figure 1: Still shot from the HABL rig as it flew over the Chippewa River and the UWEC  Campus

Figure 2: Still shot from the HABL rig over the Chippewa River in Wisconsin

Figure 3: Still shot from the HABL rig of the lower reaches of the atmosphere showing our first glimps of space. Notice the curvature of the earth present

Figure 4: Map created by Dr. J. Hupy showing the flight path of the HABL rig  during the first few minutes of flight

Figure 5: Map created by Dr. J. Hupy showing the more established flight path of the HABL rig  

Figure 6: Map created by Dr. J. Hupy showing the entire flight of the HABL rig

Discussion

            Although the footage from the balloon is very unstable due to the turbulence it experienced on its accent, some very excellent imagery was obtained by taking still shots of the video. Unfortunately though, a few unforeseen issues with the HABL rig arose. First, the Flip camera only allowed for about an hour of video to be recorded before shutting off, thus only showing the assent, bursting of the balloon, and part of the descent. Second, condensation formed on the inside of the lens part way up the accent creating a slightly cloudy, hazy image. Even though these issues reduced the overall quality of the recorded flight, the launch as a whole was seen as a great success with many useful observations made that will be applied to the next proposed HABL launch. In addition to launching the balloon on a day with better atmospheric conditions, a more rugged GoPro camera will be used to allow for a longer video to be recorded. Also, in addition to a different camera, instruments such as an anemometer, thermometer, and barometer will be on board to record atmospheric conditions along the flight.

Conclusion

            I enjoyed the launching of our HABL rig very much because of the collaboration and team work that went into making it possible. It was also crazy to thing that we sent something we made into space, and then were able to retrieve it all in the same day. Overall it proved to be a great experience, and a great way to end the semester by bringing the class together one last time to showcase our hard work.

            

Press release of the HABL launch by UWEC News: http://www.uwec.edu/News/releases/13/05/0507HABL.htm

Video created by Dr. J. Hupy of the HABL launch:
http://desi.uwec.edu/Geography/Hupyjp/Weather_Balloon_1024.asx

Lab 10: Balloon Mapping Part II

Introduction

            With the knowledge gained from last week’s experimental launch of the balloon mapping rig, we set out on our final run at creating a high resolution mosaiced map of the UW- Eau Claire campus. Methods and discussion on how images were collected on April 15, 2013 and processed later that week to generate the final mosaic will be outlined by this post.

Methods/Discussion

            Again because of the short window of time that spanned our three-hour class period, a delegation of tasks was essential. Much like last week, class was broken up into small groups who were assigned to be responsible for a single element of the launch. Aside from logistical tasks such as measuring out 400 feet of sting that would tether the mapping rig to the ground and the transport of materials down to the staging area near the shed where the balloon would be filled with helium and attached to the mapping platform, several additional tasks were added.

            My team, consisting of Laurel H., Joey Q., Hannah B., and Zach W., set out with an array of handheld GPS units to record ground control points spread out over the entire AOI for the mosaic. GPS units used for ground control point collection were a Trimble Juno, Trimble Nomad, and Topcon. Although each team member was deployed with a different style GPS unit, the same ground control points, mostly light poles, fire hydrants, and other permanent features, were collected across all platforms. When a ground control point’s coordinates were taken, they were marked as waypoints within the GPS and given an accompanying attribute to signify which GPS unit mapped it.

           Following the collection of the points in the field, they were then converted into a point feature class within ArcMap. The purpose of collecting ground control points to later be used when georeferencing is to both assign a coordinate system to the unreferenced image, and to also allow for multiple images to seamlessly be mosaiced by positioning and placing them in their correct geographic location. Although ground control points can be established by visually interpreting corresponding points such as the corners of sidewalks or other permanent features between a referenced image and the unreferenced image, the addition of GPS generated ground control points would be especially useful for georeferencing imagery collected by the balloon mapping rig because much of the campus is under construction which would not allow images to be georeferenced to a previously remotely sensed base map. As it turns out, the accuracy of these ground control points did not allow for their use when later georeferencing the aerial imagery because of the variability among GPS units that sometime mapped waypoints up to a few meters away from their correct physical location.

Figure 1: Show above are two clusters of GPS ground control points. Each group of three were mapped in the same location, but notice how spread out they are. 

            Since we were unable to use the GPS generated ground control points to georeference our images, we were left to continue to brainstorm ways to generate highly accurate ground control points. Dr. Hupy came up with the idea of using an AutoCad coverage file showing building outlines. Although it was a good idea, the oblique nature of most of the imagery generated by the balloon mapping rig did not lend itself to be georeferenced to multiple previously determined ground control points, both GPS and AutoCad generated, because using those methods alone cased a highly distorted mosaic where building edges and other linear features did not match up.

Figure 2: Building AutoCad coverage overlain on a basemap of UW-Eau Claire

            Still wanting to avoid the user friendly, cartographically pleasing, but highly inaccurate freeware program Mapknitter, I set out to devise my own hybrid method to mosaic images together. I first found an on nadir image generated by the mapping rig that was in the center of my outlined section to be mosiced. Then using a set of guidelines I learned in a Remote Sensing (Geog 328) class offered here at UW- Eau Claire to visually interpret imagery, I established eight ground control points based on permanent features located on the ground. Once the first image was georeferenced, I then matched corresponding points from that image, to other over lapping images also generated by the balloon-mapping rig. This new method allowed for both a cartographically pleasing mosic, but also a correctly georeferenced one as well.

Figure 3: UW- Eau Claire campus broke up into sections to be mosaiced by each group

Figure 4: The section outlining Phillips Hall and south east corner of Campus to be mosaiced by  my team

            Once enough images had been mosiced together to cover the entire section outlined for our group, the mosic to new raster tool within ArcMap was run to create a raster mosic combining all of the input images. By carefully layering the images and placing them in the correct order within the mosic to new raster tool, I was able to avoid having the tether connecting the balloon to the ground visible on the final mosaic.

Figure 5: Final mosaic output for group 5 showing Phillips Hall,  and  surrounding south east corner of UW- Eau Claire

Conclusion

            Although our class was unable to create a perfect, seamless mosaic of the UW- Eau Claire campus, I feel that we were able to create one to the best of our ability with the resources available. Above that, the knowledge taken away about georeferencing and image mosaicing prove to be extremely valuable because it was gained through the process of group collaboration and troubleshooting which in my mind is the best way to learn. 

Lab 9: Balloon Mapping

Introduction

Due to the complex nature of balloon mapping, the task was broken up into two parts that spanned over two weeks of class. The first week, outlined by this blog, entailed experimentation with the mapping rigs created in week three. The purpose of experimenting with the different rigs prior to collecting the final imagery that would be used to create a seamless, mosaicked map of campus was to observe how the rig behaved when deployed to 400 feet and troubleshoot any problems that may arise. Preliminary methods of how images generated from the balloon mapping rig are to be processed and mosaicked will also be outlined and discussed.

Methods

            Because of the short window of time that spanned our three hour class period that required the assembly, transport, launch and retrieval of the rig; delegation of duties was essential. The class was broken up into small groups (one-four people) who were assigned to be responsible for a single element of the rig launch. To document all aspects of the experimentation day, fellow classmate Tonya O. was outfitted HD video camera to provide video footage.

            The rig used for balloon mapping would resemble the HABL platform. The Styrofoam box would hang from the helium filled weather balloon and would house a Lumix digital camera that was set to continuous shoot mode. Also tested within the same rig housing was a Flip Camera that was set to shoot video. Connecting the balloon/ camera rig to the pilot on the ground would be 400 feet of rope that was marked off in 50 foot increments to allow for observation of the balloons altitude. Once the balloon reached its service altitude of 400 feet, the time was observed to be compared to date stamps on the pictures to confirm the camera rig was shooting imagery at the correct altitude. Once deployed the pilot controlling the balloon from the ground was to experiment with different flight paths by walking around the campus courtyard.

Figure 1: Shown here are teammembers inflating the weather balloon used for the mapping of campus with helium.

Figure 2: Shown here is the balloon mapping rig suspended from the helium filled weather balloon.

Figure 3: Shown here is the balloon mapping rig at its maximum altitued (around 100ft). Notice its horizontal drift from being directly overhead due to the wind out of the NW.  

 

            Imagery generated by this experimental launch were to be mosaicked using three different approaches outlined by Dr. Hupy. The methods to be tested were a freeware website called Mapknitter, a geospatial raster processing software program called ERDAS Imagine, and ArcMap Image Processor. For each of the programs, imagery was uploaded as .jpeg files.

            Our Team consisting of Tonya O. and Chuck P. stitched the balloon imagery together using Mapknitter. After uploading an image into Mapknitter, tools within the program allowed for image manipulation. Once uploaded and projected over a  Google Earth basemap of the UWEC campus tools such as rotate (to scale the image), distort (to shift the image by dragging the corners), and toggle (to adjust image transparency) were used to manipulate the image to mimic that of the basemap.

Discussion

            After much discussion as a class, we decided to use a rig similar to the HABL platform instead of the plastic bottle prototypes generated for lab three in class. By incorporating the HABL rig into the balloon mapping exercise, testing for both could be done simultaneously. The first observation that was made was that the camera would have to be firmly secured within the Styrofoam rig housing to prevent the lens from slipping out of the slot cut into the bottom of the rig due to any turbulence encountered at 400 feet. The second observation made was that nearly windless conditions would be necessary to both get the balloon to reach 400 feet directly overhead, and to also keep the camera steady to prevent it from swinging like a pendulum. Although the line connecting the balloon to the ground snapped from such high winds, we decided that higher pound test line would not be necessary when flying it in calmer conditions. Any image that was taken as the camera was swinging would obviously be blurry, but also it would be oblique because it was not pointed directly downward; thus useless for image mosaicking. Although windless conditions would be optimal for image collection with the balloon, we observed that the addition of some sort of fin on the bottom of the rig would help mitigate its effect and allow us to fly the rig even if there was a slight breeze. It was also decided that the Lumix digital camera would be used because after processing the images from both the Flip camera and the Lumix, the Lumix took higher quality imagery.

Figure 4: Shown here is a low oblique image of UWEC taken by the rig as it swung out of control underneath the balloon.

 

            Aside from observations made from the experimental flying of the balloon, many were also made in regard to image processing. I found Mapknitter to be extremely straightforward and user friendly but I was not able to achieve the level of accuracy needed for this project by using it to mosaic the images. Although it generated cartographically pleasing maps, it lacked the georeferencing component needed to tie our imagery to ground control points which is our end goal, so either ERDAS Imagine or ArcMap Image Processor will be used for mosaicking the second time. Both programs allow for georeferencing so either will suit our needs.

Figure 5: Shown here is the mosaic output from MapKnitter overlayed on a Google Earth base map.

 

Conclusion

            Even though Mother Nature won out and snapped the line at the base of the balloon due to such extreme wind conditions, we were able to gather valuable data that will be applied to the final launch of the balloon mapping rig. By applying the knowledge gained by this experimental day, I have no doubt that a seamless, high resolution mosaicked map of campus will be generated.

Shown in the video above is the balloon rig plummeting into the river when the 400 foot tether snapped at the base of the balloon.

 

Lab 8: GPS Navigation With a Map

Introduction

            For our third and final trip to the Priory, our task was to utilize all of the methods previously explained in the posts below describing the different technology used for navigation. The objective was to find as many points as possible within our three hour lab time using whatever technique we thought was most efficient. The class was broken into six groups and the group who navigated and found the most way points was the winner. To add another variable to the competition, each team member was outfitted with a Tippmann A5 paintball marker that would be used to engage opposing groups when navigating. Due to the stigma that surrounds any aggressive looking black piece of plastic and metal that has a barrel and shoots any sort of projectile, we had to be very careful when navigating from point to point. Although Dr. Hupy cleared the activity with the appropriate University Administrators, we still had to be careful due to the fact that the Priory doubles as the University’s daycare center. We added a clearly defined “No Shoot” area to our navigation maps that specifically outlined the areas we were not allowed to be in. Since this was our third trip to the Priory and we were getting familiar to the area, staying within the new navigation boundary was not an issue.

Figure 1: Shown above is the navigation map used. It clearly depicts the "No Shooting Zone" at the Priory.

Methods

            Like last week, each team was given a Garmin E-trex GPS unit to aid in navigation. Again, the only function allowed to be used on the GPS was the real time display of the GPS unit’s current position shown in UTM NAD 83 Zone 15 N coordinates. In addition to the GPS unit, teams were also allowed to possess a reference navigation map much like the one used in lab six. By combining the two resources and using them in unison, navigation was done with relative ease.

            To again show the efficiency of each team as they moved from way point to way point, the track log function was turned on within the GPS. In addition to the track log automatically plotting a point every 30 seconds to for a digital trail of breadcrumbs, each team member was also required to manually plot a way point on the GPS once a navigation marker was found in the field.

            The score cards used to validate that a team found a way point were to be punched by a hole punch connected by a string to that navigation marker that was unique to each respective navigation marker.

Figure 2: Shown above is the score cards used to validate and record the successful location of a way point.

 

            In addition to just arbitrarily wandering from way point to way point like the previous past trips to the Priory, the addition of paintball markers aimed to up the level of completion. Teams were allowed to engage opposing teams at will but if any member of your team got hit, it was required that you cease all movement and fire for five minutes.

Figure 3: The image above shoes the paintball equipment used for this navigation exercise at the Priory.

 

Discussion

            Unlike last week, where it took our team a considerable amount of time to orient ourselves using nothing but the GPS for navigation, we were able to begin traveling to the first way point immediately. We were able to do this because of the navigation map we possessed that pinpointed our location as soon as our GPS units got a satellite fix. Once we oriented ourselves we then created a route that would most efficiently direct us to the most amount of points in the least amount of time.

Figure 4: Shown above is the track log feature class from our team that was automatically recorded by the Garmin GPS unit.

Figure 5: Displayed on this map is my track log feature class as it was recorded by the Garmin GPS unit.

Figure 6: Shown above is the way point feature class I recorded at each navigation way point located in the field. Notice the deviation due to canopy cover from the GPS point I recorded and the actual location of the navigation way points.

 

Clearly shown by the track log data for our group, a minimal amount of “zig-zagging” was done from point to point. Once a direct route was established on the map we stayed on that bearing using the compass function within the GPS. Since we didn’t have to follow the specific bearing like we did when navigating with only a compass and pace count regardless of the areas topography, we also were able to navigate around much of the nasty terrain to avoid steep hills and deep valleys. We were able to do this because we always knew our exact location within the Priory by utilizing both the map and GPS unit simultaneously.

Conclusion

            Aside with my obsession with paintball guns, I found this lab both extremely enjoyable and educational at the same time. It again provided a perfect example of how useful GPS technology and the UTM coordinate system are. It also reinforced my understanding of the UTM coordinate system by having us walk around following the UTM coordinates displayed on the GPS. By doing this, it showed again how they are simply broken down into meter increments that are northing and easting from the origin of Zone 15 N. I also like how it called upon the skills we learned in lab six on how to navigate with a compass bearing because that knowledge greatly increased our team’s efficiency in finding the predefined way points. The progression from low tech land navigation to the higher tech methods like GPS was perfect because it showed how the same result can be obtained with different methods. This wide array of skills allowed for us to not only find the way points with the least amount of energy, but also showed how important it is to have back up methods so completion of a task can be done regardless of equipment failure or malfunction.

Lab 7: GPS Land Navigation

For this week’s lab, our task was to again navigate the Priory using UTM coordinates to locate each waypoint. Instead of using the traditional methods employed in the previous session (pace count and azimuth), only handheld Garmin E-trex GPS units would be used. Although the Garmin units are relatively inexpensive and only contain basic functions, they still operate on with a reasonably high level of accuracy allowing for their use in navigational exercises.

Fig. 1: Shown above is an example of the GPS unit used to navigate the Priory 

There are multiple ways of preloading the waypoint coordinates into the GPS unit to aid in navigation, but that was not allowed for this exercise. The only function allowed on the GPS was the real-time display of the GPS unit’s current position shown in UTM NAD 83 Zone 15 N coordinates. Each team was to then wander around to find the specific waypoints based solely on their ability to reference the coordinates displayed on the GPS unit to aid in their movement to the coordinates of the predefined waypoints.

To show each teams efficiency in finding the waypoints on each course, the tracklog function on each GPS was turned on. By turning the tracklog on, points were plotted at a predetermined interval, usually every 30 seconds, to show where each group traveled by creating a digital trail of breadcrumbs. These tracklogs would then be uploaded from the GPS units and loaded into a session of ArcMap with the location of the waypoints overlaid upon them to see how accurately navigation could be done using only a GPS.

Although it took a little while to orient ourselves using nothing but the GPS for navigation, it did not take long for our group to begin to travel in the correct direction to our first waypoint. Since we had three team members, we decided to use each member for a specific task. One team member took control of finding the X segment of the UTM coordinate, another team member moved in the direction of the Y portion of the UTM coordinate, and the third team member directed the pair to move in unison by combining their respective directions of travel to find the correct bearing to the waypoint.

Fig. 2: Shown above is the tracklog uploaded from the GPS unit displaying movement from point to point on course three at the Priory.

Fig. 3: An overlay of each team members tracklog on course three at the Priory

As seen in the map of displaying our team’s tracklogs, navigation utilizing only a handheld GPS unit is possible, but requires quite a bit of energy to do so. It is clear on the tracklog maps that travel from point to point was not as the crow flies. Quite a bit of “zig- zagging” can be seen in the tracklogs because it was sometimes hard to establish a direction of travel with the X and Y coordinates both convening on the waypoint in unison. Generally, we would overshoot one portion of the coordinate and have to create a right angle from our current position to move laterally to the correct location of the waypoint.

I found this lab interesting and very useful because it provided a perfect example of how useful GPS technology and the UTM coordinate system are. By having us walk around following the UTM coordinates displayed on the GPS, it showed how they are simply broken down into meter increments that are northing and easting from the origin of Zone 15 N. Essentially we were just traversing a massive X, Y coordinate plain and once that concept was understood, navigation from point to point was simple and straightforward.

Fig. 4: All class members tracklogs displayed according to the course navigated at the Priory.

 

Lab 6: Navigation with Map and Compass

Intro

The task for the second half of our land navigation lab is to first plot the UTM coordinates of our way points on the map, and then to successfully navigate the course using nothing but a compass to plot azimuth and the scale included on our map to determine distance between the points.

Methods
To successfully navigate the course, preparing our materials was crucial due to the amount of cumulative error that could be encountered when navigating from point to point using such basic instruments.

Step 1: Point Plotting

            With our maps in had that we created in the previous weeks lab, our first task was to plot all six of our way points using nothing but the UTM coordinates. Point plotting was fairly strait forward because of our well labeled axis, and with relative ease. To help mitigate error, each team member plotted their points individually and then collectively compared them to create the final map that would be used when calculating azimuth and distance. Lines were next drawn from point to point, one through six, to serve as visual aids when determining azimuth.



Fig. 1: The way point coordinates for land navigation of the Priory were presented to us on an Excel spreadsheet. Our group was on course three and plotted the bottom six points using the their UTM coordinates.

Fig. 2: Shown here is myself and another team member plotting the UTM coordinates of our way points prior to heading out into the field.

Step 2: Calculating Azimuth & Distance

Fig. 3: Shown above is a reference image of the type of compass we used to both determine the azimuth from point to point and also to navigate the Priory.

            We used a basic field land navigation compass to determine azimuth by centering the north oriented compass over point one. Azimuth to the next point was then determined by recording the degree value where the line to the next point was intercepted on the compass bezel. We recoded each azimuth value from point to point on a chart that would later be used to set our compass to when in the field.

Fig. 4: Using a basic field navigation compass and the methods listed above, we calculated azimuth from point to point that would later be used when navigating the Priory to find our six way points. 

           Distance from point to point was determined by using the scale (meters) we included on our final map and then compared to our hundred meter pace count to determine the amount of paces needed to travel from point to point.

Step 3: Establishing Azimuth in the Field from Point to Point 

            Holding the compass close to your chest and away from any metal objects that could cause error and pull the compass needle away from true north, the first azimuth value is dialed in to line up with the heading arrow. By placing the needle inside of the red north arrow inside of the compass your bearing is set and you simply head out in the direction that the heading arrow is pointing. Using landmark objects that line up with the heading arrow you simply pace off to that landmark, re shoot azimuth to a new landmark and continue to do that with the set bearing until you reach your way point and then start the whole process over.

Fig. 5: Shown here, using the methods listed above, is a team member pacing out to a predetermined landmark that was in line with the correct azimuth to the next way point.

Fig. 6: Shown here is a team member stopping to make sure that our line of travel stayed on the correct bearing to the next way point. This image is taken from the point of view of the team member who was in charge of directing the walker to stay on course with the correct bearing. 

Fig. 7: Shown here is our team at the first way point we found when navigating the Priory using only a compass and pace count.

Discussion

            Due to the relatively short distances (<400m) from point to point on the land navigation course, any error in our azimuth or distance values was not magnified too much because our calculations put us within the general location of the blaze orange colored way points that contrasted the white snow very well. For all of the way points, we usually had a visual conformation of them within 50 meters of actually reaching them.

            Aside from using the map  to plot and calculate azimuth and distance between points, our group hardly used it at all when traversing from point to point out in the field because of the reference table we created containing the azimuth and distance values before heading out into the field. To check the accuracy of the contour lines though, we did locate ourselves on the edge of a steep ridge to see how well the map depicted the physical topography of the Priory landscape, and it did.

Conclusion

            Our team found all of the way points on our course (#3) within the allotted time given, and did not get lost in the process. I accredit this success to the preparation of our reference map, and also the amount of time we spent collaborating when plotting our points to put them in the most accurate location. The amount of preparation we spent on this lab directly fed into its success, and just goes to show how important it is to prepare and double check all parts of the task prior to heading out into the field.