Pix4D

Introduction

Over the course of the semester, the class has learned many useful techniques and strategies to help survey data in the field. Much of these techniques were learned using either specific survey equipment or more traditional methods. In this final assignment, the goal was to show how the use of UAS and software for UAS can be used to complete most of the tasks that we completed over the semester in a much shorter time. In this assignment, Pix4D was the software used to explore a UAS mission flown by Dr. Hupy over the Litchfield Mine. 

Methods

All of the data that was used in this project was provided to us by Dr. Hupy. The first step in this project was to create a new folder and paste the necessary data in it. Next, Pix4D was opened and a new project was created. Inside the new project, control points were placed to create a processing area for when an image was going to be processed from the mission. The project that was run, creates an orthomosaic and a digital surface model of the specified processing area. Once the project starts to run, it is a waiting game. The software has to process all of the images taken by the UAS during its mission and then mesh them all together to complete a full image. Once this is done, there are many different tools that you can run with the finished product. For example, you will see in the results, a calculation for the volume of one of the sand piles in the mine, the distance of a line, and the area of a specific zone on the mine. These are just some of the ways that Pix4D can be used along with a UAS to survey land. 

Results

To start off, Figure 1 shows the mission that was run by the UAS. Each red dot signifies an image being captured. Starting from the top right and snaking to the bottom left. The red box with a grey fill represents the processing area that was chosen. 

Figure 1. Shows the mission that was run and the processing area that was chosen.

Next is the results of the orthomosaic and the digital surface model. You can see that both the images are in the shape of the previously defined processing area. Figure 2 shows the orthomosaic on the left and the digital surface model on the right. 

Figure 2. Orthomosaic and digital surface model from the project.

Next, when going over the results of the process, Pix4D gives a report to notify you on how the process went. One of the helpful tools provided is Figure 3. It shows how much overlap in images there was in the processing area. The more overlap of images, the more accurate that area will be. It is ideal, in this case, to have as much green as possible. 

Figure 3. Shows the overlap report from the image processing. 

As stated earlier, there are tools that can be run once the processing has been finished. One  of the tools that was run was the length tool. Figure 4 shows the length tool run. The upper right side of the screen shot is where the results are shown. The line segment that is measured is located towards the bottom left of the image.

Figure 4. shows the length tool being used. 

Figure 5 shows another tool that was used in this project. That tool is the area tool. This tool allows you to create a polygon and measure the area within that space. The green area shown in Figure 5 represents the area that was measured. The results are posted in the top right of the image similar to the previous figure.

Figure 5. shows the area tool being used. 

Figure 6 shows the last tool that was used in this project. The volume tool. This tool, as you can imagine, can measure the volume of an object in the digital surface model. To show how this works, one of the sand piles was used. In Figure 6 you can see the mound is highlighted, and the results are posted in the top left of the image. 

Figure 6. shows the sand mound that had its volume measured. 

Conclusion

Over the course of the semester we learned many ways to survey data out in the field. From the total station survey to the ArcCollector survey, I feel that I learned a lot about the different ways of going out to collect data. This UAS and Pix4D assignment was the perfect assignment to end on for this course. It was an excellent way of bringing everything together to show the class that UAS can be one of the most useful and versatile pieces of surveying equipment that we can access. The power that they have to create mosaic images and digital surface models has changed the game. I wish that we would have been able to work with the UAS more through out this class so that we could get an even better feel for its potential. 

Topographic Survey

Introduction

This weeks assignment focused on using a survey grade GPS to take elevation data from specific areas on campus. The data was taken from a small patch of grass located in the Campus Mall. The study area was surveyed because the land was rather uneven and it would give the class a chance to utilize the high powered GPS to create digital elevation models. 

Methods

This assignment required the class to make a trip outside to collect some data. The overall study area was small. A small patch of grass located in the campus mall was used as the study area. The class used a high precision, survey grade GPS. The GPS unit was used by every individual in the class. This means that there were roughly 20 points taken to create a DEM. The survey method used was a random sample. This means that the GPS unit was moved to random areas throughout the study area to make sure that all of the points were not being taken from the top of the hill area or at the bottom of the hill. The GPS unit collected both Latitude and Longitude as well as an elevation value.

Once each student got a chance to use the GPS to survey a point, the data was transferred from the GPS to a text file. The data was then imported into an excel spreadsheet from the text file. Once there was a working spreadsheet, it was time to create a file geodatabase. With the file geodatabase, the excel spreadsheet data could be imported and used to create the DEM. This was done by importing the spreadsheet and creating a point feature class. Using the point feature class, different tools could be run to create different DEMs. An IDW, Kriging, Natural Neighbor, Spline, and TIN were all created from the points. All of these DEMs were created in WGS 1984 UTM zone 15 projection so that there is minimal distortion. With these rasters, maps were created to show the elevation changes in the study area. To finish off, these rasters were placed into ArcScene to create 3D images of the rasters to better show the elevation changes. 

Results

The results of this project include all of the different raster DEMs created as well as the different 3D images created. It is interesting to look at how the different interpolation methods change how the data is interpreted. Figure 1 shows the final rasters created in ArcMap.

Figure 1. This is the compilation of all of the rasters that were created in this assignment using different interpolation methods.

Figure 2 through 6 show how all of the different interpolation methods are different through the 3D image creation of ArcScene. 

Figure 2 shows the Kriging interpolation method displayed in ArcScene.

Figure 3 shows the Nearest Neighbor interpolation method displayed in ArcScene.

Figure 4 shows the Spline interpolation method displayed in ArcScene.

Figure 5 shows the TIN displayed in ArcScene. 

Figure 6 shows the IDW interpolation method displayed in ArcScene. 

From looking at these different interpolation methods, you can see which methods worked well for this project. Seeing as there was one larger hill on the Southern side of the raster, the method that truly best displays it is the Nearest Neighbor method. The TIN and Kriging also represent this fairly well. The issues that arise with the IDW and the spline are that you can see specific holes and mounds that do not actually exist in the area.

Conclusion

This project gave the class the opportunity to work with a high precision, survey grade GPS in order to create multiple DEMs to represent a small area on campus. This was a nice project to get to work with the survey grade GPS because we were surveying such a small area that it was very easy to visualize what the DEMs should come out looking like. It was interesting to see how different interpolation methods can change the output by so much. For example, the IDW ended up looking like a completely different area. Overall, this was a very good assignment to teach us how the survey grad GPS works and how to use it as well as refine our skills in creating DEMs using different interpolation methods and being able to interpret them.