UAS Sensors and Data Collection

Introduction The goal of this lab was to get more familiar with ARC pro GIS. I chose to fallow a tutorial on planning a timber harvest, which involved doing data analysis to Identify approximately how many trees would be harvest this season. I chose this topic as I thought it would be an interesting application for remote sensing, and would allow companies to more easily estimate harvest, therefor estimating revenue and income. Methods The method was to fallow the ARC pro GIS tutorial and the end result for the estimated harvest was to get the number of acres of aspen trees that were going to be publicly harvested and the numbers of acres that were going to be industrially harvested. The public state-owned land had harvesting limitations on the trees being older than 50 years, on more than 20 acres of land, and in a specific soil category. The Industrial owned land harvest had the trees had to be older than 40 years and that was it.  Each group has their own restrictions, so th...

Introduction The goal of this lab was to better understand the thermal heat transfer between objects and their surroundings. The better understanding of thermodynamics helps with the analysis for future infra-red (IR) data collection. Methods Figure 1. A RGB Image of the sousvide setup In this lab, the method to image the temperature change of objects to collect data on their rate of heat transfer was by placing 4 3d printed planes into a hot water bath, and imaging it with an IR camera. Three of the four planes were frozen and one was put into a plastic bag with no air, one was put into a plastic bag with air, and one was put into a wool sock. Their was also a plane which was keep at room temperature and placed into a plastic bag with air. All planes were placed into the hot water bath and the IR sensor, specifically a Zenmuse XT2 camera, watched the airplanes to see how their temperature changed over time. Figure 2. An IR image of the sousvide Results  Each ...

Introduction The goal of this lab was to get a better understanding of thermal cameras, how they work, and what they can and cannot do. The thermal camera used to capture the images was a FLIR E series.  Methods The methods for testing the thermal camera involved using it capture images, to gather data on their thermal values. Some of the things that had to be considered while capturing the images were the use of false color, and the use of overlaying thermal over electro optical (EO) images .   Their were 2 color palates that were used in the lab, Ironbow, which is yellow hot and purple for cold, and a black and white scale. The benefits of the Ironbow palate was that it was easier to identify which part is cold and which is hot as this is how one would normally expect as people have associated blue with cold and red for hot. A drawback of using the iron coloration is that some detail is lost in the process of adding the color. The benefits of using the black a...

LineVision- Ultimate Introduction The goal of this lab was to use the software LineVision to analyze a video and gather different GPS points from the video. Methods The first task was to find the GPS coordinates of the Green trees in the burn area, the location that was identified for the 3 trees, A, B and C, tree A is in the top left , below it is tree B and below tree B is tree C, the smallest. The gps points of  latitude of 40.449934, and a longitude of -87.050567 for tree A, latitude of 40.449613 and a longitude of -87.050603 for tree B, and a lattitude of 40.449298, and a longitude of -87.049173 for Tree C. Tree A and B are relatively accurate for their GPS locations, but tree C is not as their was an issue with the software that inverted the side of the camera that the location of the point was if it was below the mid-line of the horizontal. Figure 1, This image is a screen capture of the LineVision software, the 3 blue dots represent the tree locations in relat...

Introduction In this lab we were challenged to apply our camera knowledge that we learned from our first lab in a few different real world settings. We were using manual settings on a DJI Mavic Pro 2 to ensure that we had total control over the Images and we got the best results.  Methods First Object The first object that we had to take an image of was a large object in the hanger. We took an image of a white airplane on a white background, which provided a challenge as the exposure was hard to dial in and ensure that the airplanes details would not mix with the floor. We also had a dark colored engine on the airplane that provided a challenge because we wanted to also be able to see the dark details in the engine. We changed the aperture to f 3.3 and a shutter speed of 1/30 and an iso of 100. We used the histogram to help us get these settings because originally the peaks were all off to the left on auto settings, meaning the picture was under exposed so we corrected it by ...

Introduction In the camera settings lab we went thought the process of learning the camera settings with a DJI Mavic pro two. We conducted this lab to ensure that we would be comfortable with changing the camera settings to ensure that we could capture the best data for the given conditions while operating a UAS. We focused on changing the aperture, shutter speed, and the iso. We took note of what happens when each setting is changed and why one would change the settings.  Methods We first took a picture with the auto settings (figure 1) to have something to compare what happens when you change the settings on the drone. In this picture you can notice that the image has a few parts that are over exposed like the windows and the door, but for the most part this is a perfectly fine image. This photo allowed us to get a good baseline for when we changed our other settings so we will refer back to it. Figure 1, Auto Settings F2.8, SS 1/30, iso 100 Aperture   Next we...