UAS Flight

Introduction

This lab is focused on data collection using an unmanned aerial system. Unfortunately, we weren't actually able to individually set up a flight path and collect any data in this exercise, which makes writing about it difficult. Originally I was hoping to actually capture some NIR reflectance values for the Priory, however due to unfavorable weather conditions this was not possible. Therefore, this post will be focused on the steps necessary to set a project up using

Methods

When starting up the project it is important to note environmental conditions, such as temperature, cloud cover, and wind speed/direction. Today it was in the low 50s with 100 percent stratus cloud cover and winds at 4 miles per hour with gusts much higher. If environmental conditions are unfavorable it is important to postpone the project. Before begenning the pre-flight check it is important to get the project set up on the Mission Planner software. This program allows extensive customization, such as camera width, flying height, time in between image captures, and flight speed. It is important to select the best settings for the job at hand. If you are collecting data for precision agriculture you should select camera lens with a very narrow view to eliminate off-nadir image capture. If you are collecting data for a grassy field, one would be able to use a much wider camera lense and in turn take fewer flight lines to obtain the necessary data (Figure 1).

Figure 1  Mission Planner user interface. As you can see, a rectangular box is drawn on the screen. The software will then create flight paths that will ensure the entire study area is covered. Flight lines are based on camera width and flying height.

Next, we draw the desire flight path in the Mission Planner software. By drawing a rectangular box over the study area, Mission Planner takes into account the width of camera lens and other variables selected above, and creates an appropraite flight path. After the flight path has been determined we are able to start the pre-flight check.
The pre-flight check is the most important aspect of any UAS mission. If not taken seriously a malfunction in any part of the system can lead to costly damage to the UAS and time spent repairing it. The pre-flight check involves checking various boxes in the Mission Planner program. Included in the pre-flight check are tests for electrical connections, frame connections, motor connections, secure props, secure battery, and secure antenna. After the checklist has been completed the UAS is powered up (Figure 2).

Figure 2  UAV that was used to colect data in the visible spectrum.

The UAS is manually lifted off the ground. Once it gets to a safe height above the ground the operator can swith into autopilot mode. When switched into autopilot the Mission Planner software takes over and flights the predetermined flight lines. If there is a malfunction anywhere in the UAS, the operator has the power to switch back to control and land the UAV safely. After the flight has been completed, the UAV automatically lands. Upon landing the post-flight check is to be completed. The post flight check involves noting the flight time, whether any problems occurred, making sure the data was properly collected, and safely shutting down the UAV.

Results

Due to heavy winds the UAS quickly traveled off the desired path. This led to the mission being aborted shortly after takeoff.Therefore, there was very little data collected. Pictured below are a few aerials that were collected in the NIR spectrum. NIR is highly refelected by healthy vegetation due the the cell structure of the plant. Therefore, areas that appear white in an NIR image and dense, heathly vegetation while areas that appear gray and black are less healthy. NIR images are commonly given a false color. In a false color NIR image the NIR band is assigned the color red, the red portion of the image is assigned the green portion of the spectrum, and the green coloring in the image is assigned the blue portion of the spectrum. This basically turns the image a pinkish color where healthy vegetation occurs. Figure X below is the original image collected from the UAS. Unfortunately, I was unable to create a false color infrared image due to the images being a .jpg file format. Also, due to time and weather constraints, we were unable to process the data any further. If given the opportunity we would have been able to combine all the images collected into 1 much larger image similar to what is seen by landsat data (Figure 3).

Figure 3  NIR image collected by the UAV. This image shows areas of healthy vegetation as white while areas with little or no vegetation appear black. The area in the upper right of the image is the parking lot of the Priory and the area in the right of the image is a deciduous tree.

If we were to process the images further, we would be able to create a string of images that overlap each other sufficiently. We would then be able to mosiac the images together, using a histogram matching technique to create seamless images that could be used for analysis. A process like this is very common in precision agriculture practices.

Conclusion

As previously state, there was no data that was collected except a few aerial images. Therefore, we were unable to do any NDVI calculations to determine where vegetation was the most healthy, or anything of the sort. Overall, based on some of the horror stories associated with UAV crashes this mission was not a total failure in that both UAVs returned to the lab in 1 piece.