Global Mapper v24.1

Bumpy roads

p_pereira
p_pereira
in Elevation Data

Hello.

I have some vector data that represents the roads (urban and rural) of the area I'm working on. For the last few months I've been using Global Mapper to create DEM's and give elevation attributes to the vector data that my co-workers draw (in 2D). For the most part of the projects we've been working on, I've been able to get the results I need. However, for some reason, I've been getting a lot of problems in the current project.

For the last few months my workflow is the following:

  1. I classify and "clean" the point cloud (I generate DEM's as a trial and error to try and "clean" the point cloud as much as I can);
  2. When I'm satisfied with the result I import the vector data that needs a Z value and use the "Apply elevation to the selected features" (this might not be correctly translated because I use GM in my native language).

As I said, everything worked fine on previous projects but this one is giving me headaches. On this project I get a lot of "bumpy" roads and peaks, like the image bellow:

image.png

In some cases, I've noticed that it's related to the 2D drawing (my co-workers draw in CAD on top of orthophotos) that is a little bit of the road so I get peaks from points like trees or high noise that I didn't clean, but those situations are normally a small volume and easily solved. However, the volume of data I work on doesn't allow me to verify manually and individually every case so I try to automate as much as I can and focus on the more notorious problems. In the case of this project I get this peaks and bumps all over the project.

The only solution I'm thinking of is removing vertices in CAD so I can make the roads more homogeneous without changing the real elevation of those vertices. However, this would be very time consuming and I don't feel like I'll be able to get to the result I want.

Have any of you had problems with this or have any ideas that I might try to solve this?


Obs: This is a Riegl Las, and they have been, by far, the ones I get the best results with. This was also classified by A.I.. I've been working like this for a while and it usually turns out very good.


Thanks in advance!

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Answers

  • DerrickW
    DerrickW

    Try binning your lidar data, after going through noise removal. Depending on the site, MIN or MEDIAN might work best (bin settings in the elevation grid creation options, not lidar thinning).

    Tops & Toes is where the binning process is going to affect your data most/first, so take a close look at those spots as you're iterating through different bin settings.

    If your ground-classified point cloud is relatively free of noise and residual vegetation, I'd start with something like Binning MEDIAN with a 1ft spacing. Once you get up to about 3ft-5ft is where you'll start seeing it affect TOPs, in my experience.

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