Lab 3: Introduction to GPS

Introduction: The goal of this lab is to learn how to collect features with GPS and learn how to import the collected features into ArcMap in order to map them. I was to create a database, prepare it, then load it onto a Trimble Juno. After learning how to use the Trimble, I was to use it to collect point, line, and polygon features around campus. Finally, I was to import my data into ArcMap, and make a map showing my data.

Methods: First, I made a Geodatabase, which I subsequently named Lab 3. In this Geodatabase, I made six feature classes: point, line, polygon, as well as separate copies of these feature classes to use for practice. All of these feature classes were made using the NAD_1983_HARN_Wisconsin_TM meters coordinate system. I then imported a shape file of the campus buildings to my geo-database and a raster image of campus, so that I could use them as a point of reference when collecting data. I imported them using the import feature class single, and import rasterdataset tools respectively. I then changed the symbology of my feature classes so I would be able to quickly tell the difference between my two series of data when in the field.

Next, I learned how to prepare the geo-database to be added to the Trimble Juno. In order to do this I enabled the ArcPad data manager extension, with which I deployed all of the layers I made into a folder. Then I cut the folder and pasted it on the storage card of the Juno.

 After ensuring that the data was deployed properly I the Juno out to the campus commons and practiced using the Juno by capturing points, polygons, and lines into the practice feature classes. After I felt familiar with the program, I began collecting data points, polygons, and lines for the real feature classes. I used point averaging in order to collect points for light poles and trees. I also used the point averaging feature in order to create polygons of the geometrically designed green spaces, as their straight lines would allow for fewer data points. In order to craft a polygon of a decorative pavement circle in the sidewalk I used the point-streaming feature so that I could more accurately capture the shape of the feature. I then captured the footbridge between the sidewalk circle and Davies center by using point averaging to capture two vertices to make a line.

When I felt content with the data I collected, I returned to the lab to check it back into the computer. In order to do this, I used the ArcPad data manager to check the files back into the computer. After they were properly checked in, I used the feature classes to make a map of the campus commons, using an aerial photo as the basemap.

Results: Upon adding the collected data to the map, it became immediately obvious that small errors can occur frequently when collecting data points with a handheld unit. The data tended to become more skewed, as the points I collected got closer to nearby buildings. In order to compensate for these cartographic errors, I slightly shifted the positions of the affected vertices, so they may more accurately depict the desired features.

Figure 3

Sources: GPS data collected by Peter Sawall on 4-16-2014

NAIP 201X