Classify noise between flightlines

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James Carracher

Apr 4, 2024, 3:45:55 AMApr 4
to LAStools - efficient tools for LiDAR processing

I'm just wondering if something is possible in lastools. I've never personally come across anything but you never know. I do a lot of MLS processing and in it there can be a lot of noise from passing cars or pedestrians etc. Being that I will have at least two flight lines one a road (either side of the road), is there a way to classify groups of points that only exist in one flight line? Ie a passing or parked car was in one pass, but it wasn't in the second. In this case I would classify the points only in one scan as noise.

Do you think this is possible in the current suite?

What I currently do is make a buffer around the trajectory of where I have driven, and then classify based on that and a height above the ground. This works pretty well, but will only work where I have driven and won't find parked cars that have moved or pedestrians. So I was wondering if I could improve my method.


Michael Finlay

Apr 11, 2024, 1:59:09 AMApr 11
to LAStools - efficient tools for LiDAR processing
Good suggestion James. This capability in LAStools would be very useful. I have wanted this for a while. 

I have wondered if this could be done by modifying lasnoise tool. 
In theory, instead of lasnoise looking for a minimum number of ALL points surrounding the candidate point, perhaps it could consider only surrounding points with a different point source ID different to that of the candidate point. OR, it could only consider points outside a timestamp threshold, like +/- more than 5 seconds relative to the candidate point. This I think could effectivly remove scanner noise and moving objects as long as it was scanned minimum twice if not multiple times. And work for mobile, terrestrial and rapidly growing SLAM LiDAR pointclouds in our favourite format (LAZ). 

Other software appears to use a method like voxel based statistics to mark or classify single source points. Counting different point sources inside each voxel and then re classifies the (original) points within. This would also be handy for a range of different applications, not noise. eg if there is the presence of 2nd, 3rd, 4th, nth, returns, then probably vegetation. My understanding is this is not how lasgrid or lasvoxel currently works. It would be good if it could classify original points based on grid or voxel results. 

LAStools has done wonderful things for aerial LiDAR, but it could evolve to be great at terrestrial, mobile, SLAM LiDAR too by re-thinking how some tools work. 



James Carracher

Apr 29, 2024, 2:16:27 AMApr 29
to LAStools - efficient tools for LiDAR processing
I think you started to make me want it Michael when you told me about the idea years ago!

Using lasnoise in that way is something I hadn't considered before, I think that could work. I am pretty sure other software does use voxels like you said. I've never been able to work it out in that. Using it, or to a lesser extent lasgrid, you'd think that there would be a way to reclassify noise if a step/voxel doesn't have any overlap. Though it might need the flightline too so thinks too far from it (with a low density of points) don't get misclassified

Do you have any ideas Jochen/Silke?


Jochen Rapidlasso

Apr 30, 2024, 9:46:53 AMApr 30
to LAStools - efficient tools for LiDAR processing
Hi James and Michael,
we don't want to give too much away, but I think the new lascopy can handle this.
This is almost ready to deliver, you can do a copy/merge of 2 files not only by order or gps/channel but also by many other attributes, like xyz coordinates where you can separate or classify points just in one of both files.


Jochen @rapidlasso

Processing Lidar

May 2, 2024, 1:56:41 AMMay 2
"It would be a great idea if lastools manages to incorporate that feature. In my personal experience, when I need to remove noise points in terrestrial scans, what I do is use another software that allows me to separate those points using various techniques, which works 90% of the time. Occasionally, manual intervention has been necessary, but only in specific areas.

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