Tim Pruss UAS Blog

For the open source GIS lab we took the same task from a previous assignment and did it in QGIS instead of ArcMap or Pix4D. It was determined that, since Esri is so expensive, it would be prudent to learn the basics of open source GIS, which can be found for free. To facilitate this lesson, Dr. Christina Hupy was brought in to teach a lesson on QGIS. Figure 1 can explain the gist of the lesson. Figure 1: Open source volumetrics We used open source tools in QGIS to measure the volumes of piles in a quarry. An important distinction between Esri and QGIS is that in QGIS every tool is created in open source and even tools that already exist can be recreated and improved upon. This creates a bit of redundancy depending on the task you are performing but it also gives a lot of options. It seems to me that the QGIS is a very good tool to use and doesn't seem inherently inferior to Esri with the exception of Esri being more user friendly. Once someone is able to adequately navi

The second outing to Martell Forest after the disastrous ending to the first one. Since many of the notes overlapped I did not take as many as the first time. This time around, instead of being in the team that helped to set up the UAS, I was in the team that placed the GCP in strategic locations around the mission area, and thus my notes are more focused around that. Figure 1: The M600 takes flight Figure 2: Jasper, Lucas, and Hupy inspecting the gimbal Field Notes: GCP Placement: use different elevations 1st - 217 near dirt and rock pile on the road 2nd - 943 Next to road and shed 3rd - 491 Next to four cages 4th - 142 along tree edge sw corner clearing 5th - 500 along tree edge se corner 6th - 360 se . Corner bt tall grass and tree 7th - 206 along the tall grass nw of last one 8th - 420 middle middle 9th - 034 north of tall grass on east side 10th - 747 near truck. East of truck New Drone M600 Oblique 60 degrees camera angle Zenmuse x5 Rolling shutter Shutter priori

Introduction Mission planning is the preparation, information gathering, and checklists that take place before a mission begins. An important aspect of this phase is the distinction of the level of autonomy that the UAS will have. A more autonomous mission will likely have more of a focus on planning because there is less direct control over the UAV and thus you are unable to react as readily to unpredicted situations. Check-lists are a major part of pre-flight planning. A checklist will help ensure that all the necessary steps are completed and done in order, removing the chance that you could simply forget a step. Working with the C3P software For the first part of this lab we were asked to create a couple missions in varying conditions. The first example was a mission that followed along the length of a road as seen in Figure 1. Figure 1: Road Mission That mission was created in the Bramor Test Fields in Slovenia. Because it the mission takes place in a flat area, the

Introduction In this lab I was subjected to the tedious work that is processing oblique imagery. The process involved manually removing pixels from images so that only certain objects remained once a 3D model was processed using Pix4D. Oblique imagery is imagery that is collected by taking pictures at an angle (rather than straight down like for nadir). Nadir is normally used for mapping large areas while oblique imagery is good for seeing the sides of three dimensional objects like structures or landmarks. Annotation in Pix4D is removal of unnecessary parts of images that are not desired in the final product. There are three different types of annotation in Pix4D that are discussed in the tutorial. Mask: The selected pixels are not used for processing. The description for this one is vague and, quite frankly, I'm not entirely sure what it is meant to do. Its listed used include removing an object that appears in the in a few images and removing the background of an othop

Introduction In this lab we planned to gather data with an H520 (Figure 1) UAV equipped with the E90 Yuneec Sensor. The GCPs we used were Aeropoint Markers and were positioned around the field.  The class was split into two different groups, in the interest of saving time. One group would observe the preflight portion where Professor Hupy readied the UAV while the other group would go with Evan to position and activate the GCPs. I, in the preflight group, observed the compass calibration, and the accelerometer calibration by Hans and Hupy while Hupy explained what he was doing and what to look for. Once the GCP group got back, we were just about finished with the preflight and ready to fly. Professor Hupy asked if anyone wanted to fly and Lucas agreed to do it. The UAV started up without a hitch, ascended to about 30m, began to move along it’s preprogrammed path, and proceeded to drop to the ground. The payload/ camera with gimbal somehow remained intact but the rest of the UAV was n

Introduction In this lab I used an online tutorial to calculate engage in "Value Added Data Analysis." I essentially used ArcPro to calculate the aerial impervious surface area of a given map. The tutorial that I used can be found below. https://learn.arcgis.com/en/projects/calculate-impervious-surfaces-from-spectral-imagery/ Methods: This lab is a bit odd in comparison to the others in that it relies on sampling and AI to perform calculations. In Figure 1 you can see the starting image, apparently a neighborhood near Louisville, Kentucky. Figure 1: Pretty standard map Segmentation I started off by segmenting the image for easier classification. To do this, I had to start by extracting the spectral bands by using the "Raster Functions" in the "Imagery" tab seen in Figure 2. Figure 2: Raster Functions Using the extract bands function found in raster functions and the combination "4 1 3" the original image was converted to what c