Making maps with the help of small UAVs seems to be easy enough. However, when geometric accuracy is critical, how do you determine and state the estimated accuracy of your mapping product? One way is to establish a test bed with a redundancy of accurately surveyed check points which are used as independent bench marks against which the map can be compared. In this picture we show a comparison between high accuracy GPS derived check point coordinates and corresponding coordinates as derived from our 3D model. Note that for illustration purposes the horizontal errors were scaled by a factor of 1000.
The 3D model was created from 261 aerial images (13mm GSD) captured by a Sony a6000 camera with 16mm fixed lens. The camera was carried by a Pixhawk equipped modified Steadidrone quadcopter. The flying time was 10 minutes and, using our V-Map system (http://www.microaerialprojects.com/v-map/ ), we could accurately survey the 12 ground control points in about 15 minutes.
Using 105 check points in our error analysis we can now confidently claim that when we map similar terrain with this particular method we can realistically expect to achieve the following accuracy:
Horizontal approximate circular error at 95% confidence 0.028m
Vertical Accuracy at 95% confidence: 0.039m
Not bad, especially when considering that the 4.75ha map can be delivered the very next day after image acquisition.
Comments
As always, very nice work Walter!
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Very interesting. Have you run any tests in tall grass or another non-hard landcover? You essentially tested absolute accuracy of the system but my guess is that both horizontal and vertical accuracy radically decreases in a tall vegetation. I've done a lot of research and my thesis looking at LIDAR accuracy in tidal wetlands and even with lasers we struggle to find the ground surface.
@Martin: Maximum horizontal error was 0.041m, maximum vertical error was 0.063m. But a point by point comparison is not really the whole story here. Due to the extremely high density of points on the surface - some 1800 of them per square meter - and the fact that their errors appear to be random - you get a much more accurate model than you could economically get from RTK. The test field was chosen because it contains permanent road markings that can be used for ground control and check points (hence no need for target maintenance) and because it represents a surface that is typical for a lot of as built survey work on roads etc. The size of the job is small but that is where the niche lies for UAVs - small jobs ordered today and delivered tomorrow. Also, there is enough data in those 4.75ha to keep a CAD jockey busy for at least a day.
@Luke - no, sadly i'm not that witty! Pretty amazing that you were able to demonstrate with water.
This is probably a dumb question, but I assume that since this was inside, this was using control points only, and just for scaling? I'm surprised that the concrete texture was good enough for the SfM to work its magic.
And, I can commiserate - one of my customers has a large frozen goods warehouse - kept at -7F - it is awkward to get frostbite in the middle of the summer when it is 90F outside!
@Marek: The camera was fixed to the air frame. Hence all images are near nadir. Pitch angles up to 8 degrees, roll values up to 4 degrees - as derived from Agisoft's PhotoScan. The job was controlled by 12 classic ground control points (which were excluded from the error analysis).
@me: For this exercise I used the mean of two independent dual frequency GPS post processed solutions (carrier phase ambiguities resolved) to obtain coordinates for the GCPs as well as the check points. You are absolutely right when you say that my errors are within what you would expect from a classical RTK survey. In fact, the SfM results could be used to verify the GPS survey - that is how good they actually are. A huge amount of survey work is done by RTK and this little test shows that SfM is just as good, if not better than RTK. Now go try and tell that to the survey profession. ;-)
Is that a pun, Dan?! Funny thing was that we did the survey during summer and we almost died from the heat trapped in this super insulated space!
Luke, how cool is that? Pretty impressive.
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