Lab 3: Introduction to GPS

The objective of this lab was to become familiar with the Trimble Juno GPS unit and create a geodatabase with feature classes and prepare that geodatabase for deployment to the Trimble Juno unit and collect field data and then proceed to check in attributes collected and make a cartographically pleasing map using data collected.

 Methods:

First step was to use ArcCatalog to create a new geodatabase and add feature classes (points, lines, and polygons). Feature classes were assigned the coordinate system NAD_1983_HARN_Wisconsin_TM (meters) and I added a field type and set it to text for all feature classes. Next a shapefile of the campus buildings and a raster of campus was imported from existing files. All elements of the new geodatabase was added to the map and the symbology of feature classes was changed accordingly to be easily distinguishable on the Trimble Juno unit. Then I saved the map.

Second I prepared the geodatabase for deployment to the Trimble Juno for field data collection using ArcPad Data Manager Toolbar. I clicked the Get Data for ArcPad and clicked the Action Menu to change the defaults of the Background Layer Format and choose AXF layer and changed the Background layer editing and choose editing allowed. Finally I chose Checkout all Geodatabase layers and copyout all other layers (making sure all layers were set to check out). I named for a folder to store my data and adjusted the path of where the file will be stored. I then finalized deployment by clicking Create the ArcPad data on this computer now and then finish.

Third I loaded the Geodatabase onto the Trimble Juno using a USB cable and cutting my folder with new geodatabase out of the directory and pasting it into the Geog335CHUPY folder on the storage card. I then confirmed that everything was checked out properly by opening my map in ArcPad on the Trimble Juno unit and seeing the campus image and building along with all the layers I created in the table of contents.

Forth, I then collected point, line, and polygon features in the field using ArcPad on the Trimble Juno GPS. The objective was to collect six polygon attributes (three using point averaging and another three using point streaming), one line of the footbridge, and six points (three with type “tree” and another three with type “Light Post”). Collecting points was easy, simply tap the point feature and point averaging will begin, after that I filled out the attribute form and clicked OK and moved on to the next point I wished to collect. For polygons I tapped the Add GPS Vertex which creates the first vertex after point averaging and repeat this step for each desired vertex. When the polygon was complete I tapped Proceed to Attribute and filled out the attribute form. I also used this method of collection for my Line feature. For point streaming I tapped the Add GPS Vertex Continuously and walked the perimeter of my polygon and tapped Proceed to Attribute to complete the polygon.

Finally I reconnected the Trimble Juno to my computer and copied my folder from the Storage card and pasted it back into my Lab3 folder.  From ArcPad Data Manager Toolbar I used the get data from ArcPad tool and checked all of my feature classes and clicked Check In. The Data I collected in the field can now appear in ArcMap. From here I designed a layout with appropriate map elements.

Results:

Here are the final results of my data collection using the Trimble Juno GPS unit. Unfortunately the raster image is an outdated image of campus which has since undergone renovation as can be seen by the overlapping elements of campus buildings and my collected data. I'm pretty sure I collected the wrong footbridge when I was supposed to collect the one crossing over the Chippewa River instead of Little Niagra Creek. The three polygons using point averaging include the largest grass area and the two immediate grass area to the right. These polygons have straight edges as opposed to the point streaming polygons which allow for more curvature and the true shape of the grass area to show. At the beginning of my data collection session I had a PDOP of around 3.8 probably due to the cloudiness and my orientation to nearby campus buildings. As time went by I was able to connect to more satellites and my PDOP eventually went down to 1.4 which I was quite satisfied with given the weather, it was very cold and windy! As shown the GPS unit has some fault and inaccuracy, for instance I know for a fact that the lower right light Post is located at the edge of the polygon and not on the path. This was probably because this was my first attribute collected when my PDOP wasn’t as low. But never the less the lesson learned is that a GPS is rarely 100% accurate and should be taken into account when collecting data.