Pix4D

 Introduction

We were introduced to Pix4D over the span of 2 weeks. The first part was to get comfortable with the tutorials and help information and the second week was about the data processing. The software can be pretty demanding when it comes to processing and required us to use the computers in lab to complete the assignment. Pix4D has 4 steps it goes through when processing the data, Initial processing, analyzing the quality report, point cloud and mesh, and DSM.

Processing

The software looks for GPS points and starts arranging the photos accordingly. If any issues arise then it will show up in the quality report. In the quality report, the software will point out any issues with the data before it continues with the processing. Next, it goes through and starts meshing the images together. Finally, the software gets to the final stage where it has all the images put together and ready for viewing. Figure 1 here is an example photo from one of the processes. This is what the final product looks like.

Figure 1: A processed Raster

Final point clouds

Depending on how many images are taken will depend on how clear the processed photo will come out. Figure 2 is of a Raster that only had 15 photos. This made the picture have a lot of black space where the resolution wasn't good enough for the program to make an exact copy of the area. Next, there was a raster that included photos taken on angles. This didn't impact much of the processing and also made the image have "holes" within it. This can be seen in Figure 3. Finally, there was a Thermal Raster that we had to process. Due to the file type, it cannot show in Pix4D but after we transfer the file into ArcGIS the image can be seen. The Raster that was from this is Figure 4, The triangles at the top are where the photos were taken but again due to the file type, there is no image below. 

Figure 2: A Raster with only a few photos

Figure 3: A Raster with photos taken not at 90 degrees

Figure 4: The invisible thermal raster

GCPs

We then looked into using ground control points to give more accurate positing data for the images. This can be useful if the images aren't geotagged with an onboard GPS. After inserting the GCPs into the data you need to reoptimize the point cloud in order to take into account the GCPs. Once they are imported you must tell Pix4d where the GCP is on 4 images, this gives it some reference points to figure out exactly where the GCP is in relation to the images taken. Figures 5,6,7 are of 3 different aircraft and with 5 GCP points. There were 6 GCP points available but due to the lack of images in some of the data, it could cause the mapping to be messed with if it was included so there are only 5 GCP points. After the project is done being reoptimized you then should re-check the quality report to ensure that the geofencing box has a green check, ensuring that the program knows where the points are. Figure 8 is of this table and because it knows where the points were to a close degree.

Figure 5: A6000 images with GCPs

Figure 6: Mavic 2 Pro images with GCP

Figure 7: XT2 images with GCP

Figure 8: Green Checks within the report

Conclusion

By using Pix4D one can create very accurate 3D models that can be even used for measuring specific parts. The one drawback of this software is the hardware requirements and if your computer is on the low end you could be processing the images for a very long time.

Datums

 Introduction

Within this lab, we were taught the importance of data collection and to ensure that the data that is collected is right. The first and most important thing is the metadata of the flight, this contains flight-critical data such as the time of the flight and what aircraft did the flight. The next most important thing is that the GPS data that is gathered is in the right format, as reversing latitude and longitudinal numbers can give one drastically different locations on Earth. 

Ground Control Points

Before a flight Ground control points (GCPs) are place around the area. These give accurate position data to the aircraft and allow for fixed points where the data was gathered. The coordinates are given in an XYZ style that the computer then can use to place the point precisely in space. X is longitude, this makes sense as the X-axis on a graph goes in the same direction as longitude lines, Y is the latitude and again follows the same reasoning. Z is the vertical distance.

Ellipsoid vs Ortho

There are two different types of height measurements within aviation. These come about due to the fact that the Earth is not a perfect sphere and there are different ways to measure the height of the aircraft. If you ask a pilot what are the two measurements they would say mean sea level (MSL) and above ground level (AGL) this corresponds to the ellipsoid and ortho measurements, but it is important to get them right as flipping them might cause an accident or poor data collection as a result. Ellipsoid height is the difference between the actual earth surface and the ellipsoid thus its AGL, while ortho is the height compared to average sea level (MSL). Figure 1 shows an image of how ellipsoid and ortho heights are taken.

Figure 1: Ellipsoid vs Ortho

Conclusion

Datums are very important when it comes to gathering data. When you have to gather location points and determine the altitude it is important that you use the right measurement. By using ArcGIS to process your data you can see if there are any issues with the data. In completion of this lab it was obvious that it is important to take down the data and in the right way, as if we didnt have the proper GCPs within the lab all the data would have been trashed.

Measure Ground Control

 Introduction

Measure ground control is an application that is meant for the future UAS company to be able to manage data collection, its fleet, and safety for all flights. Its base software is built on Airmap, an airspace service that digitally tracks important flight information. This allows the app to do critical functions to ensure that the flight is done right and safely. Personally, I feel that this software is a great start for any UAS company that has to gather data and does so with a team mentality.

Roles

There are many roles within the app and they all do different things. This makes it so that people only get the information that they need and not a whole lot of "fluff" that could cause them to get distracted. The first role is an Admin, they are responsible for adding roles and flight plans. Next is the pilot, they can view flight plans and collect data. The data analyst's job is to take the data gathered within the app that the pilot gathered and process the data accordingly. Finally, there is the drone program manager role, They can see al the missions and control when what mission is executed. All of these roles work together to form all of the stages necessary to do GIS work.

Flights

When managing flights the app has a few different options. The pilot in the field can access their assigned missions and can start and stop missions. They can also see other pilot's missions so they can be aware of other flight ops that might be happening in the area. The flights have a few different options as well. There are grid flights, useful for gathering data of a wide area and there are waypoint flights, useful if you are going to fly a pipeline or phone line for inspection. The app can manage the camera settings or if required you can tell it to use manual settings that the pilot will program in during the flight.

Safety

 Airmap updates with weather and TFRs and because Measure is built on this it also has those features. Finally one of the last but most important things that this app includes is LAANC authorization. This is Low altitude authorization and notification capability, this notifies other aircraft and ATC that there are drone ops taking place within an area so that manned aircraft can be routed around if required. This clearance can also be requested within the app and by giving your name, flight plan, aircraft, and duration of the flight, along with your 107 number. This means that the flights that the UAS organization is conducting are done safely and within the law.

Conclusion

Measure ground control is a great application that provides a skeleton structure for any up and coming UAS company to have a place to start and a way to manage its employees. It also ensures that the right data is gathered and in the safest way possible.

Exploring the ESRI Landsat App

Introduction

In order to get better acquainted with viewing satellite imagery, we explored the ESRI Landsat App. This app allows one to view satellite images that were taken all around the globe. They also can use false colors to view specific things within the image. Depending on the bands that are selected the app can do a series of different views, each one causing different things to become visible. Figure 1 shows the options one can use within the ESRI Landsat app.

Figure 1: Views available within the Landsat App

Exploration

Agricultural Rendering

The first view that was used was the agriculture view. This used false color to show where vegetation is and whether or not it is healthy. Figure 2 is of an area around Purdue, while using this agriculture view it replaces the color red with infrared. Healthy vegetation shows up as red in this view as water will hold IR energy and radiate that. Based on how much IR energy the plant is radiating will determine how red the plant shows up.

Figure 2: The Agricultural view around Purdue

Water Index

The next view that the tutorial had was of the water index. This view is a little different than the previous false-color image. This one takes values from many bands and uses calculations to find moisture. One can see that it uses the IR band to make these calculations as the spots on the map that showed up cyan in the agricultural view show up as blue in the water index view. Figure 3 is of an oasis in the desert. From orbit, the oasis can't be seen with the naked eye, but when the water index is turned on it stands out considerably.

Figure 3: Water Index over the Oasis

Temporal Perspective

The Landsat App also has another feature that can come in handy. The temporal perspective allows one to "look back" in time at old satellite images to see how the world has changed. Following this tutorial I looked at Las Vegas (NV) and Phoenix (AZ) Figure 4 is a side by side of Las Vegas, the image on the left is of the current view and the right image is of the earliest image available. Figure 5 is a side by side of Phoenix and follows the same positioning.

Figure 4: Las Vegas NV

Figure 5: Phoenix AZ

Further Exploration

After going through a few tutorials we were turned loose to create our own views and look at those views in different areas.  In order for the views to show up required some time for the software to process the desired band combination. Figure 6 is my first view that i created and i used the band combination 7,5,2. This caused the area to turn mostly lime green around West Lafayette so I was led to believe it was doing something similar to the vegetation index.

Figure 6: West Lafayette, 7,5,2

Figure 7 was a darker image with the band combination of 1,2,4. It was hard to tell what this one was showing so i stayed in the same spot, Ames, Iowa, and tweaked the combination to 1,4,6 and gave me Figure 8.  This one was still dark but bluer than the last which made me think that it also was highlighting vegetation just in blue this time.

Figure 7: Ames Iowa, 1,2,4

Figure 8: Ames Iowa, 1,4,6

Figures 9 and 10 are of Chicago IL and are pretty similar. The band combination used for figure 9 was 5,4,2 and caused vegetation to show up red and most of the image to darken. figure 10's band combination was 6,3,1 and just caused more red to appear.

Figure 9: Chicago IL, 5,4,2

Figure 10: Chicago IL, 6,3,1

Conclusion

By using this software it gives one an idea of how a UAS platform could better fill this role on a smaller scale. Sure with the Landsat App, one can view anywhere on the globe with any band combination one would want. The issue is with the satellite view the images don't have a very high resolution. Using a UAS platform with a multi-spectral sensor onboard could give you the same false color ability with greater more detailed resolution.