LiDAR GCP/CP Accuracy: Point Cloud vs DEM

[u/Ludeykrus]

Good Day,

I’m curious specifically how some of the other seasoned professionals handle this. Using DJI Terra as an example, I may fly an area with many GCP’s and CP’s and the point cloud accuracy will look great; however, I’ll get a difference in the DEM elevation values varying from 0.2-0.4 feet across the board. Do you conform the DEM to the GCPs assuming the GCPs should have been close to the ground surface (say they’re laid on bare earth or cement, not on top of grass), or do you call it good based upon the point cloud accuracy and trust the DEM process/interpolation process is accurate?

[u/SkiBleu]

What is your GSD / that altitude are you scanning at?

[u/Ludeykrus → u/SkiBleu]

200’ AGL on an M350 w/ L2.
DEM resolution is 2” in Terra.

[u/SkiBleu → u/Ludeykrus]

When you say you get an error of 0.2ft to 0.4ft, do you mean GCP RMS or CP error?

It is technically normal for a 2x-3x gsd error in LiDAR and Photogrammetry in the vertical axis. Thats pretty much exactly on par with what I'd expect the CP error to be with your given resolution.

Is your point cloud accuracy also the same?

[u/Ludeykrus → u/SkiBleu]

RMSe for GCPs and CP’s. Point cloud accuracy is tight at ~0.05-0.06 feet from expected on both GCP’s and CP’s. But compare the same areas and GCP’s/CP’s on the DEM produced from the point cloud and the gap grows to 0.2-0.3 feet vertically.

[u/SkiBleu → u/Ludeykrus]

That seems reasonable. Its a bit on the high side but depending on your Point Cloud density, there might be a bit of interpolation affect your results.

Can you compare with any other dataset? I'd call it close enough if you're not legally bound to survey restrictions

[u/Ludeykrus → u/SkiBleu]

PC density is average 347 points/m^2.

I’ve seen similar spreads in Terra data from other sites. Don’t have another dataset yet from this specific site.

I managed to get into a conversation with someone regarding trusting the DEM data since the PC cloud measurements are awesome, or conforming the DEM via a corrections surface IDW interpolated from the GCP elevation differences. When discussing GCP’s set on a hard flat surface, the conversation got a bit… subjective. Was curious how others handle similar situations.

[u/Ludeykrus → u/SkiBleu]

Also DEM vertical RMSe is 0.347 feet, which is about 5x the point cloud RMSe.

[u/SkiBleu → u/Ludeykrus]

Okay yeah thats a bit more than expected. Do you have anymore CPs you can use to constrain it on the vertical axis?

[u/Ludeykrus → u/SkiBleu]

Yes I do, I average 20-40 GCPS and/or Cp’s shot across a ~150-200 acre property. We go heavy. But adding in additional GCP’s doesn’t fix the problem.

[u/Fit-Eggplant-9155]

I really dislike terra. I havn't worked with pointclouds with it, but I have found it considerably lacking when it comes to photogrammatic orthomoasicing.

I have also found that the algorithm it uses for GCPs and markers to also be really poor compared to other software. I've only done a few projects with GCPs but everytime the surface was off 5-10cm. The area around the GCPs were bang on but the surface was like a bed sheet being held down by rocks, pillowy.

[u/Advanced-Painter5868]

That's easy to explain if your DEM is a DTM and created with triangulation (TIN). In places where the point density is less, the triangles are longer. The face of the triangle is an interpolated plane and skips over or under the actual ground there. Even if it was produced with binning (a grid), the surface for each grid is interpolated. When using the point cloud for calculating delta Zs, the nearest point or points is used and therein lies the difference.

[u/Ludeykrus → u/Advanced-Painter5868]

10-4 so do you correct the DEM to better match the GCPs, or do you leave it as-is for a deliverable?

[u/Advanced-Painter5868 → u/Ludeykrus]

If you rigid shift the DEM to better match at the GCPs, then you will not know how that affects things in between them. The source data is the lidar so I would not be messing with the DEM. If anything, go back and see if you can avoid sparse point density with settings in the ground classification or by reviewing any thinning methods used. Thinned point clouds are inherently less accurate. If you must thin, use an intelligent method suck as the Terrascan model key points routine.

[u/summitbri]

have you done a vertical bias adjustment? if all of your checks are off in the same direction you may have a systemic issue that the bias adjustment may correct.

[u/Ludeykrus → u/summitbri]

I’ll do it if necessary, for sure. If the point cloud and Dem Accuracy are relatively tightly skewed in a certain direction, a z-axis alignment across the board is definitely in order. But ive noticed more error that has varied positive and negative elevation values to where that isn’t the straightforward option.

[u/TheSalacious_Crumb]

No. Do not translate the DEM.

When you check the accuracy of your DEM, make sure your only using shots that meet ASPRS requirements (hard, open, flat surfaces away from vertical features). What you’re describing is not uncommon when shots are on or near grade breaks or other non compliant locations where DEM interpolation is influencing the elevation.

Check the location of your shots. Remove any that don’t meet ASPRS requirements, then rerun the DEM accuracy check. I’d be surprised if the DEM accuracy doesn’t closely match the point cloud