Global Mapper v26.0

fit lidar data to control points

I see GM has a tool to check control points to Lidar data. This is very nice. There is also a tool to "fit lidar data to control points". This is supposed to rectify the entire cloud to match the control points.

My question is: How does it do it. What is the method. I cannot find any reference about this. I realize it will do some sort of data fit that warps existing cloud elevations. But how does this fit spread and join to the next control point?


I have bare earth ground classified points, so all other are removed already. I have survey control. I am happy to adjust the cloud to the control - but want to better understand how it is doing it. Not just a magic button. Once I rectify the data it all changes. Meaning some good data could be getting worse and some poorer data gets better. Exactly how far reaching I cannot tell. I don't see any documentation.

Anyone know the answer to this?


By the way - I am dealing in 0.2ft or less of miss to ground control. SO I don't really need to rectify - but if I do - what and how is it applying the adjust!!

Best Answers

Answers

  • We also need to know this information.
  • I would like to know this as well, please. 
  • Did you ever find an answer to this? I am curious how this works too.

  • I actually just compute the shift as an average. I use GM to aid in this. I make a DEM and then load control points. Have control inherit values off DEM and then compare list 1 to list 2 in spreadsheet. And average is the shift. The standard deviation is the precision. I only use points on hard surface.


    But i think since this original thread, GM might have been updated. and you can select the method of adjust?


    3. Rigid, with translation - all the lidar points or shifted globally, there is are no local adjustments made around the control points.



    so I accomplish the above '3' by myself. So never noticed this as an option. i prefer my method because I filter the control points by code and make decisions which to include. Also I look how many standard deviations some points are and will remove them as likely outliers. Control has error as well!


    I use the t-distribution to compute the 95% certainty as a number of standard deviations. This helps when I have few control points.