Lab 12: UAS Data Processing with Ground Control Points

Introduction

In Lab 10, the UAS data collected in Lab 3 was processed in Pix4D without the use of Ground Control Points (GCPs), and had datum errors. GCPs help to improve the spatial accuracy of the data. They are visual markers, as described in Lab 3, that are surveyed so that the exact spatial coordinate is known. Aerial photographs will capture GCPs whose coordinates can be used like a push pin to tie the image to the selected datum. In this lab, the UAS data from lab 3 is processed with GCPs in Pix4D. 

Pix4D Tutorial

Using Pix4D with Ground Control Points is a very similar process as running without, except GCPs need to be added and verified. I created a new folder for this lab, and executed a "Save As" to that folder so that the initial processing data was not lost.

I then opened the GCP Manager by clicking on "Project" and "GCP/MTP Manager" which opens the window in Figure 1. On the right side of the window, I clicked "Import GCPs" to import a table of the coordinates for each GCP. In lab 3 each GCP was surveyed via a variety of Global Positioning Devices. The data set used in this lab was collected with the Trimble and massaged before use. This action populated the GCP/MTP Table. Notice that the left-most column is populated with zeros, denoting that each coordinate has not yet been paired to any images. The values in this column should be at least 2 before reprocessing the data. On the bottom of the window, I clicked "Basic Editor..." which allowed me to manually click on each GCP in each image. With this process, I effectively "pinned" each image to a datum.

Figure 1: GCP/MTP Manager

Once the tedious task of identifying GCPs is completed, the GCP/MTP manager can be closed and the project can be reoptimized for GCPs. On the upper ribbon, click "Process" and then "Reoptimize." The data can now be processed. On the lower Processing Ribbon, make sure that 1. Initial Processing is NOT checked, this is an unnecessary task that will consume a lot of time. 2. Point Cloud & Mesh and 3. DSM, Orthomosaic, and Index should be checked so that a DSM and Orthomosaic can be produced. This will take a lot of time.

Data Discussion

With the use of GCPs, the Digital Surface Models and Orthomosaic are more spatially accurate than without. Figure 2 shows the improvement of horizontal accuracy when GCPs are used to create the DSM. I used "Spatial Accuracy" feature class created in Lab 11 by delineating the leftmost side of major roads near the mine site to compare the spatial accuracy of the two Orthomosiacs. Figures 3 and 4 show the greatly improved vertical accuracy of the Digital Surface models. Recall in Lab 11 it was discussed that the DSM without GCPs put elevation between 80 and 105 m AMSL, when the true elevation is approximately 234m AMSL. In ArcScene DSM with GCP and DSM without GCP were both displayed in the same viewer. There is a large visual gap between the two.

Figure 2: Spatial accuracy of Orthomosaics. Left: Orthomosaic generated with GCPs overlain by "Spatial Accuracy" feature class, perfectly delineating the leftmost side of major roads near the mine. Right: Orthomosaic generated without GCPs overlain by "Spatial Accuracy" feature class which does not line up as it should.

Figure 3: Vertical Accuracy of DSMs Oblique View

Figure 4: Vertical Accuracy of DSMs Crossectional View

A secondary educational goal of lab 3 was to test the accuracy of cell phone GPS. Figure 5 shows a site map of all 16 GCPs collected with Trimble. Figures 6 and 7 zoom into sites 6 and 7, respectively, comparing GCP coordinates collected with Trimble, Topcon, Bad Elf GPSs, and Cell Phones. You can see that Trimble and Topcon are right on top of the GCP cross hairs, but the Bad Elf and Cell Phone data is less accurate, up to 8meters away from the correct location.

Figure 5: GCPs collected with Trimble

Figure 6: GCP Collection Comparison at GCP no.6

Figure 7: GCP Collection Comparison at GCP no.7

Conclusion

The real world purpose of collecting and processing this data is to eventually be able to calculate the volume of stockpiles at the mine. Volume is a product of basal surface area and height, and thus depends greatly on the spatial accuracy of elevation and surface area data. Based on the two tests conducted, GCPs significantly improved the horizontal accuracy, vertical accuracy, and overall quality of the data. To conduct UAS surveys with integrity, one should always use ground control points.

Pix4D made it relatively easy to add GCPs, verify them, and process the data, as long as the GCP data was well maintained and organized. This exercise was a good reminder to manage data properly.