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High absolute camera position and orientation uncertainties Z component

With the use of Pix4Dmapper so far, we have not encountered any problems that I will briefly try to describe, so please help.

An area with low altitude differences (flat area) was captured with dji phantom 4 advanced in 2 sets of photographs with a flight height of 75 and 160 meters. In the initial processing of both projects, a high value of mean Z component of the absolute camera position and orientation uncertainties was present in the report: for the mission with 75 meters 0.208 m and for the mission with 160 meters 0.183 m (in this mission new parameters for camera had to be used because of high difference between initial and optimized internal camera parameters and restart the first processing step was needed). After processing 2nd and 3rd steps (after loading the GCPs and reoptimizing) the Z values for the 75 m mission was 0.429 m, while for the 160 m mission was 0.772 m.

Part of the subject area was recorded using classical surveying methods, and there is a large discrepancy in the height of the captured details and the same details from both models, the details of the models from photos from 70 meters are on average 15 cm lower from the same details taken by the classical surveying methods, while the details of the models from photographs from 160 meters are on average 30 cm higher than the same details taken by classical methods. The height difference of 2 models is approx. 0.5 m

In attachment I am sending you quality reports for initial processing and model for both missions.

19_SELNICA KAMING 75 inicial report.pdf (1.5 MB) 19_SELNICA KAMING 75 report.pdf (1.6 MB) 19_SELNICA KAMING 160m initial report.pdf (2.2 MB) 19_SELNICA KAMING 160report.pdf (2.3 MB)

Hi Damir,

I assume you did not acquire an RTK/PPK image dataset. If your dataset has been acquired with a consumer drone that relies solely on a standard GPS receiver, then the absolute accuracy will lie within a few meters. Note that image geotags are usually measured with an accuracy between 5 m (X, Y) and 10 m (Z).

In projects with image geolocation and without GCPs, the absolute camera position uncertainty will be similar to the expected GPS accuracy. As all images are positioned with similar accuracy, the sigma reported in the table should be small compared to the mean (which is also your case). The absolute camera position uncertainties are also expected to be bigger than the relative ones in the table Relative position and orientation uncertainties.

Long story short, the absolute geolocation table refers to the absolute difference between the image geolocation (geotags) and the final optimized position. In your case, I would recommend using GCPs. GCPs are definitely more accurate and reliable than image geotags recorded with standard GPS. They make the model more robust and accurately georeferenced. If you are using GCPs, it is likely that some of the cameras will be moved significantly with respect to the initial geotags. This would be expected due to the low accuracy of the image geolocation.

Hopefully this helps.