Thanks for sharing the new link and for the description.
I noticed two points in the quality report:
- Camera optimization
If we have a closer look at the individual camera models from each subproject:
a) Seems ok.
b) Large differences about 46%
c) Smaller, but still large differences about 8%
d) Smaller but still large
e) too large
In summary, I would verify in the subprojects if the camera optimization is green in the quality report summary (<5% change). If not and as the camera is a known camera in the Pix4D camera database. I would suggest to use All Prior in Processing Options > Initial Processing > Calibration > Internal parameters optimization. This tells the software to stay closer to initial parameters during the optimization.
- GCP accuracy
The default accuracy values of GCPs are 0.02 meters. If you have a project in feet, the accuracy of the GCPs needs to be adapted. In this case, if you’d like to keep the default values it should be 0.066 ft. Also, I would verify the marks you have added for the GCPs in the images, as there seem to be very high errors, especially on the Z axis.
The accuracy of the GCPs can be edited in Project > GCP/MTP Manager. I would make sure that each subproject is well processed with these parameters before merging them.
These two points should already significantly improve the project, please post updates once you could try them.