Field Navigation Map

Introduction
This week's assignment is preparing the class for a field navigation outing at the University's new daycare center, a few miles south of campus, denoted by the place marker here in Fig. 1.

Fig. 1

The total land area that this exercise will take place on is approximately 112 acres in size and consists of hilly and woody terrain. A high resolution aerial image is shown in Fig. 2 with a red boundary box denoting the area in which various points will be placed for the class to navigate to.


Fig. 2

For this exercise, we won't have any fancy navigational instruments such as a GPS, but rather we will be relying on the old school technique of map and compass to find various points scattered around the plot of land. Often times, a GPS might lose it's signal if one is in dense vegetation or maybe the batteries will run out when in the field. Then what? It is vital to be able to navigate without reliance on technology. Knowing how to use a map and compass is a fail proof way to ensure that if in a sticky situation when technology fails, one can find their way to any point on the map. Teams will be split up into teams of three, so once in the field, one person will be walking, the second person navigationg the walker, and the third person manning the compass and map. Each member of the group is responsible for creating a map (front and back) on an 11" x 17" piece of paper. Out of the three, we will agree on which one we will use for the field navigation exercise.

Methodology
The first thing we did in preparation for the navigation exercise was to go outside and conduct a pace count. Essentially, a pace count is a way to count how many steps one takes in a 100 meter stretch. This will become extremely helpful since we won't have a GPS unit to establish an exact distance for us. It should be noted that we conducted the pace count on a sidewalk to get a true 100 meter distance. However, it is also apparent that once in the woods, we won't be able to walk in a straight line, therefore we will have to add a few paces to our own pace counts to adjust to the situation we will face in the woods. Everyone did the pace count at least twice so that we could average our paces if they were off each time we did it. My personal pace count was 67 paces per 100 meters. Also, the reason that we did this exercise in meters is because our maps will utilize a UTM coordinate system which also measures distances in meters.

That being said, let's talk coordinate systems for a bit! Coordinate systems are the single most important part of making a map. One must know which coordinate system is best suited for their area of interest or else the map could become useless or even work against you. Most people are familiar with the standard latidude/longitude coordinate systems, but rarely should this coordinate system be used outside of making a small geographic scale or global map. This is because latitude and longitude cannot be used to measure precise distances which are needed in a navigation situation. Thus, for surveying or navigation uses, a coordinate system suited for a large geographic scale are necessary. The most popular and useful are UTM and State Plane coordinate systems which allow meter precision. A UTM coordinate system breaks the world into longitudinal based strips or zones in order to minimize distortion. More information on UTM coordinate systems can be found here: http://egsc.usgs.gov/isb/pubs/factsheets/fs07701.html.
A State Plane System is a coordinate system developed specifically for each state. The only problem with this is that this system is still considered to broad for an area like the one we will be doing our field activity on. A State Plane system is best suited for an area covering most of a state or an area falling between two UTM zones within a state. We decided that utilizing a UTM coordinate system would suit us best for our exercise. The exercise area falls into UTM zone 15 and we will use the NAD83 datum for reference.

The next step was to compile all of the data we will be using for making our map into a file geodatabase in ArcMap so that we could run the Arctools and spatial analysis tools on the files. Our geodatabse consists of: shapefiles for navigation and point boundaries, orthoimagery of the area of interest, surveyed 2 ft. contour lines, and also a DEM. After getting all of the data into the geodatabase, it is necessary to get all of the data into the same projection so that further analysis can be done accurately. Once again, we wanted to get all of the data into the UTM 15N projection. This is where we hit a bit of a speed bump with the surveyed contour data. This data was in a CAD format and lacked any spatial projection reference as shown in Fig. 3.



Fig. 3

 

 

 

We were unable to succesfully define a projection for this dataset, so we had to follow a specific order of adding layers. First, we had to add our projected orthoimage which then set the data frame projection to UTM 15N so that if any more layers are added, they are automatically projected on the fly to UTM 15N. This does not mean that the projection is defined or changed for the CAD file however, it just allows the dataset to overlay where it should if it had a defined projection of UTM 15N. This is a really nice feature of ArcMap. It is suggested though that even though a dataset lacking projection properties that is projected on the fly, one cannot do any further analysis until the projections are the same in the properties window. To avoid this headache, our group decided that we did not really need to use 2 ft. contour intervals, so we scrapped that dataset. What we did instead was use the DEM and run a spatial analyst tool to make contours set at whatever interval we wanted. We chose to use 2 meter intervals because this size interval will still give us elevation detail but not clutter the map up so much. Fig. 4 shows how cluttered the 2 ft. contour intervals would have made the map. 

Fig. 4

Since the elevation range in this area is from 245m - 312m, it is really not necessary for our purposes to have this detailed of contour lines because it just makes the map more confusing and busy which will distract from effective navigation. All of the various datasets were clipped to fit the Navigation Boundary box so that there was no extra, unneeded data showing.

The map that I made, which was chosen for the group map, is detailed in the following paragraph and images.
For the one side of the map (Fig. 5), I wanted just a basic, clean map showing the contour lines along with the prominent man-made features of the landscape: the Children's Center, two houses in the SW, and a holding pond to the NE highlighted in orange. The purple contour lines are the 2m contours and the green contours are 5m contour lines. I was also able to label each contour line for quick reference. The Children's Center building sits atop the highest elevation point. The inside red square box indicates the point boundary and the outer, thicker red box indicates the navigation boundary. We included a 20m x 20m grid over the top of the map elements so measuring distances will be very easy. Other map elements include: North arrow for reference, scale in meters, and also projection information. 



Fig. 5

On the other side (Fig. 6), I chose to include the orthoimage which will be very helpful for visual reference of the landscape and also a color coded DEM to show the altering elevations of the landscape.

Fig. 6

I left the grid on top as well and then labeled both ends of the elevation legend bar which is incremented into 10m segments. The red areas are the highest elevation and the dark green are the lowest elevations. The goal was to keep the maps simple yet effective and I think that these maps meet the criteria and will be very useful in the field for navigation.

Discussion
The key concepts from this exercise include datasets, map projections, and map elements. All three are extremely important as they each contribute vital information to the map itself and also to the user. One has to decide on what datasets are most important to the map reader and then how to manipulate the datasets to show what you want as well as to create an aesthetically pleasing and useful map. Once again, projections make or break a map. Firstly, make sure to pick an appropriate coordinate system and then make sure all of the datasets are defined to the same projection to provide an accurate range of data. Map elements such as a north arrow, scale, and some sort of legend are also vital elements of map. Without these elements the map becomes very ambigous and useless. These maps will be put to the true test this coming week as we will actually be out in the field implementing them. I just hope these maps work well or my group may start a mutiny against me!