Assignment 11: Flying UAVs at South Middle School's Garden

Introduction

For this class, we headed south of UWEC about 10 minutes to Eau Claire's South Middle School Garden to fly the DJI Phantom 3 Advanced and the DJI Inspire a bit. This served as a visual and physical learning experience to see what actually goes into flying a UAV for geospatial analysis.

Methods

We arrived at the garden around 3 pm and first started by laying out the ground control points (GCPs). Since the garden was the area being flown, nine GCPs were laid out in three rows by three columns, ensuring to cover each corner of the garden. Figures 1 and 2 show the garden and a GCP placed within the garden's fence.

Figure 1: South Middle School's garden.

Figure 2: GCP laid out in garden.

The GCPs we used had numbers on them, so we made sure to put them in sequentially ordered snake pattern. From there, we used a survey-grade global positioning system (GPS) ground station that gave coordinates to the GCPs. Figure 3 shows a classmate using the GPS receiver to collect coordinates of a GCP.

Figure 3: Giving GCPs coordinates with ground station.

It was important to ensure that the coordinates were in the correct coordinate system (UTM) and that the GPS was centered over the GCP by using the balance on the receiver. After all of the GCPs were geolocated, flight was soon to come. Dr. Hupy prepared the Phantom for flight and set up the controller, explaining to the class what he was doing along the way. Before take-off, Dr. Hupy had noticed that the Phantom needed a software update and the UAS would not let us fly until the update was completed. This brought up an interesting, but real-world mishap. Luckily, we had our own wi-fi signal and we were able to complete the update while we set up the DJI Inspire.

Figure 4: "Mi-Fi" personal Wi-Fi hotspot.

Finally, after completing the software update, the Phantom was ready to fly. Here is a video of the phantom's take-off from the first flight:

The first flight was an aerial coverage of the garden, and the second flight was an oblique (camera set at 75 degrees) coverage of the class's cars. After two successful flights with the Phantom, we moved to the DJI Inspire; a bit heavier and more powerful UAV. Figure 5 shows a classmate attaching the rotor blades on the Inspire and figure 6 shows a classmate holding the two different sensor options we have for the Inspire.

Figure 5: Attaching rotor blades to Inspire.

Figure 6: Two sensor options for the DJI Inspire.

The Inspire was put into the air and manually controlled. The flight did not collect any imagery, however. Each classmate got a chance to fly the drone for a short period, applying the skills we've learned from the real flight simulator.

Results

The imagery from the first flight was processed in Pix4D, and produced an orthomosaic and digital surface model.

Figure 7: Orthomosaic map produced with imagery from flight one.

Figure 8: Digital Surface Model map produced with processed imagery from flight one.

Discussion

Looking at figure 7, the orthomosaic imagery offers a fairly crisp and detailed rendering of the garden, and the different agricultural plots are distinct and identifiable. I chose not to include the basemap as the orthomosaic image was inaccurately placed in some parts of the extent. This is interesting, because in the digital surface model (DSM) displayed in figure 8, the imagery appears to line-up fairly well with the basemap. Some of the color displayed in the imagery is a bit off as well, specifically the ground beneath the trees that line the garden. The image makes these areas appear a vibrant maroon-ish color, when in actuality, these areas are not as saturated.

Looking at figure 8, the trees (shown in bright red) are a bit distracting to the area of interest; the garden. While an accurate representation of the surface elevation, the sheer height of the trees takes away some of the elevation exaggeration that could be present in the garden. It is interesting to see the slight elevation change near the east side of the imagery, however. The DSM did turn out quite well, despite the somewhat interfering tree line, and shows in great detail the surface elevation of the area.

Overall, being able to see the entire process of analyzing data collected from a UAV was incredibly exciting and engaging. Everything from making the GCPs used in the field, to flying the drones, and processing the imagery, really puts the whole process into perspective.

Assignment 10: Making Ground Control Points

Introduction

For this assignment, the task was to make ground control points (GCPs) for field use of future UAS flights. The GCPs were constructed from 4' x 8' sheets of high density polyethylene. This material was used so that if the GCPs were left in the elements, they wouldn't damage like wood or some other material. The polyethylene is also relatively cheap, heavy enough that it won't move from wind, and still lightweight enough to easily transfer to a site and place.

Methods

After all was said and done, 16 GCPs were made. The first step was to cut the sheets into 8 equal squares. This was done with a table saw (figure 1).

Figure 1: Cutting polyethylene sheet.

 After the squares were cut out, a plywood triangle template was used along with magenta-colored spray paint. The template was used twice, on either side of each GCP, to create an easily distinguishable "X" on the square. From there, a number was added to the remaining black portions of the GCP so that the GCP can be easily referenced when processing the imagery.

Figure 2: Painting the GCPs.

The GCPs were left to dry for 24 hours or so, and now are ready to be used in the field.

Discussion

Overall, the process of making GCPs with Dr. Hupy was fairly easy and enjoyable. In total, there were around 12-13 people, so probably "too many cooks in the kitchen". Nonetheless, it took around 45 minutes to make 16, good looking GCPs, so the process was fast and easy.