Pix4D Processing with Ground Control Points

Introduction

This lab was meant to bring understanding to why there is a need to have ground control points when taking aerial photos with a platform.  The ground control points (GCP) add an extra level of accuracy to the final project than without them.  For this lab the same data was used as the last Pix4D lab except GCP were added into the equation to create a higher quality dataset.

Methods

The first step is to open up a new project in Pix4D and create a folder to save everything for the project in with a decent naming scheme to help organize the information.  Next, add the images like the previous Pix4D lab.  Make sure the camera is on linear rolling shutter before starting the initial processing. After the initial processing is over, go to Project ---> GCP/MTP Manager.  This open up a screen that will allow the user to upload the GCP file (Figure 1). For this GCP file the order needd to be switched to Y, X, Z due to where the Y value was placed in the .txt file.  This should be double checked before going on to save time later after secondary processing has taken place.

Figure 1: Showing what the imputed GCP will look like. 

Next, there is a problem that starts to happen.  The GCP are not tied to the ground well making the pictures and GCP appear that they are floating.  This is not the easiest problem to fix, but it can be fixed using the basic editor or the rayCloud Editor found at the bottom of the GCP manage.  

Now, to tie down the photos, the user needs to go through 3-4 of the points to correct the ground control points (Figure 2).  For the rayCloud editor, go through each GCP and for the first few images fix the location of the point.  Once that is completed selected automatic marking and then apply.  Continue this for each GCP.  Finally, once accomplished rematch and optimize the dataset (Figure 3).  

Figure 2: Ground control points being fixed by the ray cloud editor. 

Figure 3: Showing where the rematch and optimize tool is. 

Next. after the rematch and optimize the 2nd and 3rd steps need to be done on the processing.  This is going to take little while, therefore it is good to plan some other work to be done at this time due to the time needed to process.  Once it is done it will have connected the GCPs to the ground along with the images (Figure 4).  

Figure 4:  This image shows the ground control points and images connected to the actual level of the ground.  

Now, there are two ways to deal with having two sets of data for this project.  First of all, with only two sets it can be done with both of them at the same time for processing, but if there are more data sets than 3 or 4 then a merge needs to be done to allow faster processing times or just as the project is completed over multiple days can still be added to the first project.  This is done on the first screen by selecting the merge project instead of new project.  Finally, once the Orthomosaic is finished it can be opened in ArcMap where it can be made into a cartography pleasing map (Figure 5).  

Results

After all the processing is finished the newly created DSM can be brought into ArcMap where a finished project can be created for the viewer to see the data.  This map has turned out slightly more accurate than the map created in the first Pix4D lab which is a result of using the ground control points.  There is more detail made along most of the sand piles in the located in the right center of the map.  The area with the most distortion also has been limited to the area instead of having long dragging areas its more of just lobes on the bottom.  This only would have been fixed competently if there would have been more images taken in this area.  The elevation is also at its lowest point near the water which makes logical sense.  

Figure 5: A Map created from Pix4D using Litchfield Flight 1 and 2 Data. 

Conclusion

Ground control points are a great tool to have more accuracy on the finished project than without having any GCPs at all.  There are also needed when merging two different projects from the same location together to generate a more cohesive map.  Also, having fieldnotes with location of the GCPs drawn out and also having a list on the computer of each of their location would be a great idea for a back up plan if for some reason all of the data was lost or corrupted.