Agisoft Metashape
Agisoft Metashape => General => Topic started by: LFSantosgeo on December 15, 2017, 03:29:00 AM
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Hello!
I would like to know how PhotoScan handles two flights with different altitude above ground. I have two flights with good overlap between them as I'm able to process them together. I also have GCP for the imaged area but they are unable to be used in separate processing (have good coverage for the whole area but not for the individual flight's coverage). So what PhotoScan does:
1. In terms of GSD as it depends on the altitude when processing it all together?
2. When generating reports for the whole project (including both flights) it outputs a mean value for all?
How can I assess if their overlap or different GSDs contributes somehow to the error/accuracy for the point cloud?
Any comments, suggestions, ideas, experiences?
Thanks!
L.Fernando
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Hi lfsantosgeo,
PhotoScan is calculating an 'average ground resolution' (or 'average ground sampling distance'). The GSD for each project (even if it only consists of 1 flight) is variable because the distance between the sensor and the object is never constant (unless you map a perfectly flat plane and your UAV is flying perfectly at a constant height). Therefore, the GSD is variable throughout your project.
In the case of a nadir UAV survey, for example, the roof of a tall building will have a higher resolution (=smaller GSD) than the car that is parked next to the building.
Regards,
SAV
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Thank you for the reply SAV!
Once I process all and both flights I'll have a better picture of this and I'll post it here.
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On both flights the altitude above ground were closely fixed despite the differences on terrain altitude (more than 200m of unevenness) due to DEM terrain tracking.
Flight #1:
Flying altitude: 60.4 m
Ground resolution: 2.62 cm/pix
Camera stations: 88
Tie points: 66,031 of 69,358
Projections: 154,798
Reprojection error RMS: 0.326 pix
Reprojection error MAX: 9.201 pix
Mean key point size: 2.43 pix
Effective overlap: 2.38
Using geotags. Xerror: 0.61m, Yerror: 0.98m Zerror: 0.55m, Total error: 1.29m
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Flight #2:
Flying altitude: 86.9 m
Ground resolution: 3.77 cm/pix
Camera stations: 60
Tie points: 62,454 of 65,961
Projections: 151,253
Reprojection error RMS: 0.582 pix
Reprojection error MAX: 16.528 pix
Mean key point size: 4.05 pix
Effective overlap 2.50
Using geotags. Xerror: 1.10m, Yerror: 1.73m, Zerror: 0.93m, Total error: 2.26m
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Flights 1 + 2: (processed together)
Flying altitude: 70.2 m
Ground resolution: 3.04 cm/pix
Camera stations: 149
Tie points: 130,728 of 138,234
Projections: 312,085
Reprojection error RMS: 0.483 pix
Reprojection error MAX: 16.308 pix
Mean keypoint size: 3.26 pix
Effective overlap: 2.463
Using geotags. Xerror: 0.86m, Yerror: 1.40m, Zerror: 0.91m, Total error: 1.88m
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Merged chunks from individual processed flights 1 and 2
This uses the PS feature of Workflow > Merge chunks.... (merge tie points)
Flying altitude: 71.2m
Ground resolution: 3.09 cm/pix
Camera stations: 148
Tie points: 128,485 of 135,319
Projections: 306,051
Reprojection error RMS: 0.471 pix
Reprojection error MAX: 16.528 pix
Mean keypoint size: 3.23 pix
Effective overlap: 2.44
Using geotags. Xerror:0.85m, Yerror: 1.34m. Zerror: 1.58, Total error: 1.74m
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Chunks aligned + merged from individually processed flights (chunks) 1 and 2
This uses the PS feature of Workflow > Align chunks... Then, Merge chunks.... (merge tie points)
Flying altitude: 71.2m
Ground resolution: 3.09 cm/pix
Camera stations: 148
Tie points: 128,485 of 135,319
Projections: 306,051
Reprojection error RMS: 0.471 pix
Reprojection error MAX: 16.528 pix
Mean keypoint size: 3.23 pix
Effective overlap: 2.44
Using geotags. Xerror:1.76m, Yerror: 1.38m. Zerror: 1.36, Total error: 2.62m
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From the results on the last post I can figure some conclusions out. Can anyone comment on it?
1. Comparing flights 1 and 2 from different altitudes: there's an error increase within the reprojection with the increase average flight altitude above ground. This is expected as the detailed terrain features are less recognizable on each aerial image making the image matching more difficult for the SIFT identifier and descriptor (mean keypoint size). With the higher altitude the higher value of ground resolution GSD. That's also reflects on the positioning error of the aerial images with a relative higher value of total error with the higher altitude above ground flight #2.
2. As expected processing both flights at the same time leads to an average value of GSD (3.04 cm/pix), mean keypoint size and all other parameters. But they are slightly different comparing with when you merge the differents flights with the Merge chunks... tool provided in PS. The parameters of the merged chunk are much more close in value with an arithmetical average between values of flights 1 and 2 than the processed all together one.
3. The RMS reprojection error and total error in the images positioning by SIFT + SfM algorithms with the merged chunks from individually processed flights are slightly lower in 2.48% and 7.45% respectively. Thus the number of tie points is also lower than the processed flights 1 + 2 in 1.71%.
4. Aligning chunks from flights 1 and 2 before merging them only affects the cameras positioning errors. Cameras locations were substantially degraded: the total error value increased 50.57%!
Final:
As first impression there is not a big difference when processing individually different flights and merging them or processing all together. In my case I need to process them together because of GCP distribution as I only have 7 and they are unevenly distributed on both flights (for both flights together maybe they're ok).
Seems that the error differences between those two ways of processing both flights are caused by the different number of tie points identified. Aligning before merging chunks affects the cameras locations and in this case degrading the positioning.
Am I missing something?
Is there a way on PS to calculate the overlap between flights?