Navigation Map I

INTRODUCTION
Navigation in the field is incredibly important in field methods.  Accuracy in the field is dependent on the type of navigational resources available and can be skewed with the simplest miscalculation.  In the upcoming weeks, our class will be navigating through and plotting waypoint locations at the Priory, a newly acquired property for UW-Eau Claire.  Before we can set out in the field, we had to create a navigation map and determine a pace count for our group.

METHODS
To navigate in the field, each person had to calculate their pace count.  A pace count takes into account how many steps a person takes within a given distance.  This information allows a person to know how far they have traveled without the use of a GPS unit.  The distance for our pace count was 100 meters.  To determine my pace count, I walked at a normal pace counting every pace (every other step) for a pre-measured distance of 100 meters.  I repeated this process three times and took the average of the count-70 paces.  Knowing my individual pace count will help me to account for the distance I travel while navigating at the priory.

We will use two navigation maps locate our positions while in the field.  The first map will be an overview of the area, while the second will be more precise and include topography.  The maps will be printed on 11 X 17 sized paper, so before we could begin, we had to change our paper setting to match.  Our professor provided a wealth of data in the form of a geodatabase to use in our maps.  The data included CAD drawings, aerial imagery and polygon feature classes.  Topographic data was also provided by the USGS.  Maps can hold a wealth of information, but too much can cause confusion for the map user.  This was a challenge in the creation of our navigation map.  Although we wanted as much information as possible, we also need to be able to easily read and use our map.

I used an aerial image of the study area (The Priory) as the background of my first map (Figure 1).  I applied a topographic line feature class of 5 foot contours from the USGS as the next layer of the map (Figure 2).  I negated the 2 foot contour lines of the CAD drawings for this map to avoid clutter.  This first map will be used for an overall locator, so precision wasn't the highest priority.  The next layer of the map was a polygon feature class showing the boundary of the waypoints in the study area (Figure 3).  This data was also provided in the geodatabase.  The rectanglur polygon feature class had to be projected to the NAD 1983, UTM Zone 15N to correspond to the other map layers.

Figure 1- Aerial image of the study area (The Priory- Eau Claire, WI)

Figure 2- Aerial image with 5 foot contours and labels

Figure 3- Waypoint boundary polygon

A UTM coordinate system grid was applied as the top-most layer of the map.  This grid can be created in ArcMap by choosing "Data Frame Properties"> "Grids" and creating a new grid (Figure 4).  The spatial reference of the grid had to be set to NAD 1983, UTM Zone 15N (Figure 5).  Other grid properties were customized for visual necessities and units of measurement (Figure 6).  Figure 7 shows the UTM grid that was applied to the first map.

Figure 4- Creating a new UTM grid

Figure 5- Grid units

Figure 6- UTM coordinate system spatial reference

Figure 7- Newly created UTM grid with 50 meter units

 Once the map and UTM grid was created, other pertinent information was applied.  This information included a north arrow, scale bar, the projection and coordinate system of the data and data sources.  Figure 8 shows the final product of the first overview navigation map.

Figure 8- Overview navigation map

The second navigation map was created to have more precise topographic data.  The same data was used as in the first map, but I added a CAD drawing provided by the professor.  The CAD drawing consisted of 2 foot contour lines.  This was the "bottom-most" layer of the map and the same 5 foot contour data layer was applied as the next layer (Figure 9).  The symbology of this map was critical to ensure the visibility of both the 2 foot and 5 foot contours lines.  The 5 foot contour line data was labeled as a reference to the elevation.

Figure 9- 2 foot contour CAD drawing with 5 foot contour data layer

After applying both contour data files, the polygon of the waypoint boundary was again placed on the map (Figure 10).  The UTM grid was applied once again as well with the exact parameters as the first navigation map (Figure 11).  The same reference data was also applied including the projection, coordinate system, study area, data sources, north arrow and scale bar.  Figure 12 shows the second navigation map for more precise topographic representation.  The aerial imagery was not used for this map so the contour lines would be more easily visible.

Figure 10- Boundary polygon with contour data

Figure 11- UTM grid with 50 meter units

Figure 12- Navigation Map with 2 and 5 foot contours

DISCUSSION

Although the process of creating navigation maps seems quite simple, the importance came from the application of data.  The maps needed to present all necessary information, but ease of legibility was also critical.  By using two maps this asset could be maintained.  Each person in our group of three created their own two navigation maps and we voted on the best maps to use in the field.  We chose Zac Womeldorf's two foot contour map (Figure 13) and Phil Glodowski's aerial locator map (Figure 14).

Figure 13- Zac Womeldorf's 2 foot contour map

Figure 14- Phil Glodwoski's Aerial locator map

CONCLUSSION

Knowing how to find data and knowing what the data represents is critical to map creation.  Aerial imagery can be found using NAIP imagery or Google imagery.  The USGS hold a wealth of topographic data, but it can also be found from other sources like the Wisconsin Department of Natural Resources.  GIS data is available from numerous sources, but it is best practice to use data that complies with National Map Accuracy Standards.  These standards ensure that the data creator, data lineage, projection and other pertinent information are provided with the data.

It is important to know how to navigate using a pace count and how to create a navigation map because these techniques do not require a high level of technology and they can be used in a variety of data collection methods.  The maps will help us to locate our position at The Priory and to navigate while collecting waypoint data.  They will also serve as a base for the creation of our next maps that will include waypoint data points.

Conducting a Distance Azimuth Survey

INTRODUCTION
Survey technology has dramatically improved in the last few decades.  Surveyors have a variety of tools at their disposal that allow for increased accuracy and efficiency, but sometimes technologies can fail.  In this activity we used a range finder and compass to conduct a distance azimuth survey.  The devices we used can come in handy when other resources are not available.  Our study area consisted of a 1/4 hectare plot on the new campus mall at the University of Wisconsin-Eau Claire.

METHODS
OBJECTIVE I

The first objective of this activity was to familiarize ourselves with the tools.  I worked with a partner, Phil, throughout the entire project.  We went outside behind Phillips Hall at the University of Wisconsin-Eau Claire and used a laser range finder as well as a compass to collect distance and azimuth of trees in the area. The distance was taken in meters and the azimuth was taken in degrees.  We recorded the point data in a notebook.

After we had become familiar with both devices, we used Microsoft Excel to create a table of our point data.  The initial fields were simply "SD" (Slope Distance) and "AZ" (Azimuth).  We imported this table into a file geodatabase and added it to a blank ArcMap document.  Because we did not use a GPS unit to collect the X and Y coordinates of our origin point, we had to add an aerial basemap and locate our position.  When I located our origin location, I used editor to add an X and Y field in our table.

The next step was to use the "Bearing Distance to Line" tool in ArcToolbox in the Data Management-Features folder. This tool creates a new feature class with line features calculated by the X and Y locations, the bearing field (AZ) and the distance field (SD).  After completing that process, I used the "Feature Vertices to Points" tool located in the same folder as the previous tool.  This tool creates a point feature class from the vertices of the newly created line feature class.  These new points represented the location of the data points (trees) that we collected.  To my dismay, the tree data points were located miles from the actual site location.  After some troubleshooting, Phil and I realized that our origin coordinates were not specific enough for accurate representation.  To overcome this, we changed the Data Frame Properties in ArcMap so the Display Units were decimal degrees.  I then used the Identify tool to click on the origin points on the aerial image.  This gave me X and Y coordinates with 6 decimal places, which was specific enough to accurately represent our data points.  The slope distance and azimuth are represented by the blue lines and the trees are represented as the lighter blue circles in Figure 1.

Figure 1-Test data represented in ArcMap

OBJECTIVE 1
After we had become familiar with the range finder as well as functioning in ArcMap, Phil and I conducted another distance azimuth survey.  This time, we collected data points for the stone benches located in the new campus mall.  We used two origin points, the steps of the library and steps on the south side of Schofield Hall.  The benches were located in a somewhat large area with a south-western slope.  By using to origin points, we could ensure the accuracy of the slope distance and azimuth angle.

Again we used the range finder to collect the Slope Distance (SD) and Azimuth (AZ) for each bench.  When the range finder could no longer accurately measure the SD and AZ of the benches, we moved to the steps of Scholfield Hall.  While collected the data, we had to keep a close eye to make sure we did not skip benches or collected benches twice.  We wrote the SD and AZ measurements in a notebook while collected the data and then transferred this data into an Excel spreadsheet.

Because I had run into errors on our previous attempt to import the spreadsheet into ArcMap, I created ID, X and Y fields directly into the spreadsheet.  I opened ArcMap and used the Identify tool to locate the X and Y coordinates of our origin locations (Figure 2).  This data was then pasted into the spreadsheet in the corresponding fields.  The ID field was generated simply by assigning a number in numerical order to each data point (Figure 3).

Figure 2-Identify tool in ArcMap

Figure 3- Excel spreadsheet for
bench data points

Once the Excel table was normalized, the table was imported into ArcMap and the "Bearing Distance to Line" tool was implemented (Figure 4).  After the new feature class was created, the "Feature Vertices to Points" tool was used (Figure 5).  This created a point for each bench we had collected.

Figure 4- Bearing Distance to Line tool

Figure 5- Feature Vertices to Points tool

The following images show the transformations of the data from a blank aerial image to the bearing distance line data and finally to point data, the final representation of our data points, benches in the new campus mall.  The old Davies Center on campus was removed in the previous summer, but the aerial image does not show that.  In reality, the benches exist on an open courtyard.

Figure 6- Blank aerial image of study area

Figure 7-Bearing distance lines from origins

Figure 8-Point data; Final data representation

DISCUSSION
Although these tools are beneficial when technology isn't available, there are still downfalls to this technique.  When hand-eye coordination is essential to the accuracy of a tool, human error can occur.  In this activity, we had to hold the laser range finder with one hand while aiming at the benches to record the SD and AZ.  The measurements were quite accurate, but some distortion will always accompany such methods.

Another error that can occur in this method is the duplication of information.  Below are images that seem to show this error, but the scale of the map had to be changed to show that the data points did not overlap (Figures 9, 10, 11, 12).

Figure 9-Image showing a zoomed out view
with overlapping data points

Figure 10-Image showing a close up of the
data with no overlapping data points

One must know how to overcome magnetic declination while taking a distance-azimuth survey.  Magnetic declination is the angle between true north and magnetic north which changes over time and differs on location.  Complex algorithms must be used to calculate the magnetic north because it is constantly changing.  It is necessary to know, calculate and use magnetic north while using a compass, otherwise angles could be very skewed.

CONCLUSION
This survey taught me the possibilities of somewhat simple data collectors like a compass of laser range finder.  Technology can fail in one way or another; knowing how to collect data with alternative resources is very important in the geospatial realm.  Distance-Azimuth surveys are also beneficial because sometimes extreme technology isn't needed to collect data and create an informational product.  The skills learned in this activity can be applied in a vast array of ways and can be applied to a variety of different formats.

Balloon Mapping Part I

"Preparation for the Field"

INTRODUCTION

Our Geospatial Field Methods class will be launching two balloons for mapping purposes.  The first balloon launch will be a mapping balloon to map the newly reconstructed campus mall at the University of Wisconsin-Eau Claire.  The second launch will be a high altitude balloon that will capture aerial imagery of the area surrounding the launch point.  In order to have successful launches, we worked together as a class to construct the balloon rigs and to plan the future steps of the launch.

METHODS

Figure 1-Reviewing
Reference Materials

Our class reviewed reference materials provided by our instructor before planning the execution of our balloon launch (Figure 1).  This allowed the class to gain a better idea of what exactly we would be doing and what equipment would be needed.  The instructor had supplied the equipment needed for both balloon rigs as well as a scale.

After we reviewed, the class formed groups to concentrate on specific aspects of the launch:

                -construction of the Mapping rig

                -construction of the High Altitude rig

                -Parachute Testing

                -Payload weights of both rigs

                -Design of implementing continuous shot on the cameras

                -Implementation and testing of the tracking device (Figure 8)

                -Filling the balloons with helium and securing the balloon to the rig

My group concentrated on the payload weights of both rigs.  We had to measure each and every item so when it comes time to construct the rigs, we will know exactly how much the rigs weigh.  We weighed both balloons, the parachute, two carabineers, all three cameras and memory cards, every type of rubber band, small and large zip ties, rope, string, empty liter bottles, hand warmers, Styrofoam, a “minno thermo” container, and a yellow cord with a metric scale.

Figure 2- My group weighing items

We also took pictures of each item and gave that picture a detailed label that matched the payload spreadsheet.  These pictures were uploaded into the class folder so each student has access to the images.  This is important because there is a large number of items and everyone in the class needs to know which weight corresponds to which item.  The total payload for the High Altitude Mapping Rig was determined by the end of the class period and was added to the payload spreadsheet(Figure 9).

Figure 9- Weight Chart

While my group weighed the items, other groups tested and timed the parachute, constructed rigs for both balloon applications, determined the best camera for each launch and designed the implementation of the continuous shot (Figure 3) and tested the tracking device.

Figure 3- Implementing Continuous
Shot

Figure 4- Building the Mapping
Balloon Rig

DISCUSSION

Each group made sure to document their progress and outcomes during this activity.  In the end, the documentation will allow the entire class to build both the Balloon Mapping rig as well as the High Altitude Mapping rig.  The documentation provides a framework of what has been done and what still needs to be done before we can initiate the launches.  At the end of class time, one mapping rig was constructed, "The Hindenburg" (Figure 5).

The process of preparing for the launch of both of the balloon rigs was somewhat chaotic because there were so many aspects that needed to be considered.  By breaking up into groups, students could apply their strengths to their category.  This helped because people who were better at construction worked to build the rigs (Figure 7) or people who were better at organizing the data concentrated on the payload weights, ect.

Figure 5- "The Hindenburg"

Figure 6- Balloon Mapping Rig

Figure 7- Construction of the Rigs

Figure 8- Testing the Tracking Device

The class had to work together to share the equipment because each group needed every item throughout the class period.  We also worked together to communicate to other groups what we had accomplished and what still needed to be done.  At the end of the class period, all of the groups should have recapped what was accomplished so everyone was on the same page.

CONCLUSION

As stated earlier, this is just the first step in our class’ balloon launching.  The data and designs we came up with will be improved upon and then implemented into the balloon launches.  It was a team building activity for each group and for the class as a whole.  This will help in the future steps of this process because a strong team will be needed to overcome the possible obstacles for this project.

The next steps are to design how we will fill the balloons with helium and then connects the balloons to each rig.  Once this is determined we will be able to move onto the fun part-the launch!

Digital Elevation Survey-Revisited

Introduction
This week, we revisited our "Digital Elevation Survey" activity.  The goal was to refine our survey area and tweak our methods for the best representation of our terrain.  Before we could refine our data, we imported our X and Y coordinates into ArcMap.  In ArcMap we used the IDW, Kriging, Natural Neighbor and Spline Raster Interpolation tools to visualize the terrain.  We also used ArcScene as a 3D interpretation.  Below is an image of the Spline technique in ArcScene (Figure 1).  This method was the best representation of our terrain.  The spline tool uses a 2D "minimum curvature technique" to interpolate the raster surface.  This tool differs from the other because the resulting surface passes through the input points exactly and creates a smoothing effect.

Figure 1-Spline Interpolation of the first digital elevation survey

Methods
Once we had visualized our survey, we came together as a group to discuss ways to better our research.  We decided to tie string at 10 mm intervals on the Y axis so our coordinates would be more precise (Figure 4).  The next step was to replicate the activity from the previous week.  Because it had snowed, we had to recreate our terrain (Figure 2).  After the terrain was recreated, we tied the string at 10 mm intervals on the Y axis (Figure 2 and 3).

Figure 2-Creating the terrain

Figure 3-Tying string at 10 mm intervals

Figure 4- 10 mm intervals on the Y Axis

  

After the string was tied, we began to collect our survey data in the same process as before.  For most of the survey, we took X, Y and Z coordinates at 5 mm intervals.  This would give us more data points and therefore a more precise digital elevation survey.  Like the previous time, we used a mobile X axis (Figure 5) to measure from X, but because we had string tied at every 10 mm on the Y axis, the measurements were more precise.  In areas where the terrain was flat, we took measurements every 10 mm (Figure 7).  We used a Microsoft Excel spreadsheet to record the data points.

Figure 5- Mobile X Axis

Figure 6-Laurel and Phil collecting data points

Figure 7- Meter stick with mobile X Axis to collect data

Once the entire planter box (112.5 cm by 224 cm) was surveyed, we converted the Excel spreadsheet into a digital copy.  We then imported this spreadsheet into ArcMap.  Again, we used IDW, Kriging, Natural Neighbors and Spline Raster Interpolation tools to visualize our data.  In the first attempt at this activity Spline Interpolation resulted in the best terrain model, this technique produced the best visual as well in the second attempt (Figure 8).

Figure 8- Spline Interpolation for the second survey

The second time we conducted the survey elevation features were more pronounced.  This was most likely because we took more data points and the data points were more precise.  The features were not vague representations the second time, they were replicated extremely similar to the real world features in our planter box.

Discussion
By revisiting our activity, we were able to use our previous data and outcomes to produce a better product the second time around.  We made two major changes between the first survey and the second.  We collected more data points and used string to collect more precise Y locations.  There is an obvious difference between the first Spline interpolation visual and the second.  The changes we made allowed for a more detailed representation of our digital elevation survey.  To make our survey even better, we could have used a measurement tool other than a meter stick.  A meter stick is rather wide, so our measurements would only account for the general elevation of a point.  If we used a thinner tool, the data points would be represented more accurately.  We were somewhat restrained from using this tool because we were instructed to use a meter stick.  Also, I didn't think of this until we were about halfway done collected the data for the second survey.

Conclusion
This activity really advanced my ability in the Geographic realm.  It is easy to sit at a computer and import XY coordinates and project them into a visual display, but it is harder to come up with your own data collection technique and import that into ArcMap to produce a visualization of our survey data.  This activity pushed me to think more critically about data collection and the importance it has on the desired outcome.  My group performed very well together.  We were able to account for each other's weaknesses and use our strengths to come up with the best possible survey.

Digital Elevation Surface Survey

Introduction

The purpose of this assignment was to create a surface terrain and survey this area without standard survey techniques.  In order to do so, we had to come up with a suitable coordinate system and survey technique that would account for our study area.  Geospatial and critical thinking were essential because only a tape measure, rope and a meter stick were available to conduct the survey.  Unfortunately, migraines don’t take class assignments into consideration and I wasn't able to attend the actual survey.

Methods

Because I was sick and unable to attend the survey, so I am using the data of my group members Phil and Tonya.  The first step in this assignment was to construct the terrain (Figures 1 and 2).  Our terrain included a ridge, hill depression, valley and plain.  This was done by hand in our study area which was planter box in the courtyard of Phillips.

Figure 2- Creating the terrain

Figure 1- Creating the terrain

The next step was to set up the coordinate system for the survey.  Before the physical collection of the survey, we had discussed what the best coordinate system would be.  We decided that the short end of the planter box became the X Axis and the long edge became the Y Axis.  When it came time to collect the X and Y measurements, my group members decided it would be best to use a mobile X Axis for accuracy.  A meter stick was taped to a larger stick for the mobile X axis.  Because the mobile X axis would be gliding on the outer wooden edges of the planter box, all elevations had to be lower than this height.  Phil and Tonya had to “shave” down some of the previously formed ridges and hills.  The Y axis also had a tape measure taped to the edge of the planter box.  This helped not only for an accurate Y measurement, but also an X measurement because the mobile X axis could be measured with the Y Axis so it was completely straight.  The origin of our coordinate system was very traditional at 0,0.

X and Y measurements were taken at 5 centimeter intervals where the surface had in increased amount of terrain features and 10 centimeter intervals where the surface was smoother.  As seen in image 3, once the measurements were taken for the length of the X axis, the mobile axis was shifted up to the Y axis.  The Z measurements were taken with a meter stick vertically placed along the terrain (Figure 4).  This was done for the entire study area.  The measurements were recorded onto an Excel spreadsheet.

Figure 3- Collecting X, Y and Z coordinates

Figure 4- Collecting X, Y and Z coordinates

Figure 4- Excel Spreadsheet

After the survey was conducted, the measurements were digitally imported into the Excel spreadsheet (Figure 4).  All Z measurements were in negative numbers, so 17 was added to each measurement.  The number 17 was added because the lowest Z measurement was -16.  This ensured all measurements were a positive number which allows for easier calculations.

Discussion

I am really disappointed that I was not able to help with the physical collection of our data.  Being absent from the most important part of an activity really shows how important this aspect of the assignment is.  My group members would not have struggled as much if I would have been there because it is a hands-on activity and as they say, “more hands make for lighter work.”  Also, it is hard to comprehend the data because I was not present in the collection.  This can be thought of in ways outside of just this assignment.  Data interpretation is essential in geography because it can manipulate the meaning of the data if it is misinterpreted.  It is essential in this activity to be present to really comprehend the importance of Geospatial thinking.  Without being physically present in the data collection, I missed out on the problems and wasn't able to suggest ideas to overcome these problems with the survey.

Conclusion

The biggest thing I have taken away from this assignment is the great necessity of being physically present in data collection of our study or survey.  Without being present, you can miss important aspects to the data and you are not able to solve problems with group members.  I look forward to revisiting our study area and hopefully the weather will cooperate so our surface terrain is similar to the state we left it.