Adding GCPs to Pix4D software

Introduction:

When Pix4D performs bundle-block adjustment on aerial images, the horizontal and vertical accuracy are dependent on the on-board GPS. Dependence on the on-board GPS can cause distortion of the resulting products. By recording the positions of features within the study area, it is possible to rectify the bundle-block adjustment to the known points and thus reduce distortion.

Methods:

In order to add GCPs to my project, I created a new project, imported my images, added their geolocation information, and had Pix4D use the default 3D maps preset. Next, I imported the GCPs using the "GCP/ Manual Tie Point Manager". After they were imported, I ran the project's initial processing. Once the initial processing was completed, I used the "GCP/ Manual Tie Point Manager" to identify the GCPs locations on the individual images. After the GCPs were identified, I ran the point cloud densification and orthomosaic generation steps.

After the orthomosaic and DSM were generated for the first project, I created a second project using the same images and same parameters, without using GCPs. Once the second project's orthomosaic and DSM were generated, I brought the products of both projects into ArcGIS in order to see how their accuracy differed.

The first step was to digitize the GCPs locations on each output orthomosaic in two separate feature classes. Next, I used the "Add XY coordinates" tool to append each point's coordinates to its attribute table. I used the "Add Surface Information" tool to add the Z value for each point's location on its respective DSM to the attribute table. Once each the coordinates were added to each feature, I used the "Join" tool to combine the tables, then used the "Table to Excel" tool to export the combined table (Table 1). Next, I opened the table in Excel, where I calculated RMSE and the average 3-D distance between the two points (Tables 2,3).

Results:

Table 1: The output from the Table to Excel tool.

Table 2: The distance between the GCP locations on the images generated
with and without the use of GCPs

Table 3: The total 3-Dimensional distance between the locations in table 1.

Table 4: The horizontal RMSE, vertical RMSE, and average value for table 3.

The error between the two surfaces was rather minor, yet noticeable in certain parts of the images. The horizontal RMSE was 1.406 cm, slightly less than its pixel size of 1.666cm (Table 4). The vertical RMSE was substantially higher, at 18.78cm.

Image 1: The locations of the GCPs throughout Litchfield Mine.

The images appeared identical at first, but closer inspection revealed discrepancies between the two (Image 2).

Image 2: Notice the discrepancy between the two images 1/3rd from the top of the image. 

Vertical error in the DSM increased as the distance from GCPs increased (Image 3).

Image 3: Elevation error and GCP locations.

At first I believed this increase in error was caused by the distance, but upon further inspection it seems the error is related to the type of feature (Image 4).

Image 4: Elevation error and feature type.

Conclusion:

The RMSE calculations indicated Pix4D's mosaics generated without GCPs have horizontal error less than the pixel size. This will be very useful for helping determine when GCPs are necessary in the future. The high vertical RMSE from the Non-GCP imagery, indicates that GCPs are truly important when recording elevation.