Dear CC-users,
i am searching for an elegant way of a "local pointcloud analysis".
I attached some example screenshots and looking forward to read your suggestions.
The scan is from an airborne lidar and i'd like to assess the quality of the scan on a road surface.
A paved road should be a sharp / crisp surface in the scan data.
The more noise and thickness the data shows the less useful it is.
What in your eyes could be a good approach to easily see areas of higher thickness, its thickness values and so on...?
From my point of view a good approach would be a segmentation first (subdivide into a grid or define a radius) and then a local analysis for each segment.
What would be your suggested steps for it?
;)
Thanks and greetings
Alex
analyse local thickness of laserscan-data || road surface
analyse local thickness of laserscan-data || road surface
- Attachments
-
- thickness (dZ) visible, but not local (watch dY)
- Bild_2021-06-22_105203.png (13.58 KiB) Viewed 1465 times
-
- side view of single segment_far
- Bild_2021-06-22_105005.png (39.11 KiB) Viewed 1465 times
-
- road segments to analyse
- Bild_2021-06-22_104822.png (66.22 KiB) Viewed 1465 times
Re: analyse local thickness of laserscan-data || road surface
You could try to compute the local "roughness" (https://www.cloudcompare.org/doc/wiki/i ... c_features)
Or use the Rasterize tool, and export the grid as a cloud with 'height std. dev.' and 'height range' in each cell:
Or use the Rasterize tool, and export the grid as a cloud with 'height std. dev.' and 'height range' in each cell:
Daniel, CloudCompare admin