Global Mapper v25.0

Pit and Spike removal from DEM

KBlocker
KBlocker Global Mapper User
edited June 2012 in Elevation Data
Is there a process for individually removing pits and spikes from DEM that will not affect the surrounding terrain elevations?

Thank you

Comments

  • global_mapper
    global_mapper Administrator
    edited June 2012
    What you could do is right-click on the DEM layer in the Control Center and select to create points at the grid cell centers, then edit the elevations of those points in pits or spikes (or just delete those points), then right-click on the point layer in the Control Center and select to create an elevation grid from that. The pits and spikes should then be removed or modified based on your changes to the points.

    Let me know if I can be of further assistance.

    Thanks,

    Mike
    Global Mapper Guru
    gmsupport@bluemarblegeo.com
    http://www.globalmapper.com
  • KBlocker
    KBlocker Global Mapper User
    edited June 2012
    I have a rather large area to work on, is there a way to create the control points just in the area of the pits/spikes?
    forgive me if this seems like a rtfm moment.
  • global_mapper
    global_mapper Administrator
    edited June 2012
    There isn't really a way to automatically identify the pits and spikes. I suppose you could load the layer twice, then set one to use a resampling method like a box averager of an appropriate size, then use File->Combine Terrain to create a new difference layer and easily find those places where the terrain deviates significantly from the local average. Nothing really fool-proof though.

    Thanks,

    Mike
    Global Mapper Guru
    gmsupport@bluemarblegeo.com
    http://www.globalmapper.com
  • Just stumbled on this when looking for the same thing.

    After thinking about it for a while, I figured out and tested a process.

    I created a surface from noisy lidar data which had many spikes. I then created contours at 0.25 m interval and intentionally kept small closed contours. I converted those to areas and then selected all ground-classed lidar points that were inside an area less than 0.2 sq metre. It took a while, but about 40,000 lidar points were detected which I classed as low vegetation. I then created a new surface with the resulting ground classed lidar points using the same settings as before. Results are shown below. Processing time was significant as original point cloud has 20M ground classed points. I would have achieved better results if I used a smaller contour interval (perhaps even 5 cm) and or filtered by larger areas as many spikes remain on the road surface. But this was just a proof of concept.