With selected buildings, infrastructure objects, plant project types there is an additional option to filter out very dense points (duplicates in 2mm 3D distance), which is necessary to create 3D models, or 2D drawings in scale 1:200-1:50. We strongly recommend using this function.
As an example, a terrestrial laser scanner is collecting very dense points near the scan station. Basically, you don’t these points. Lighter point cloud – smoother performance.
|Data with 2mm filtering
(Total point count: 18 863 247)
|Data without 2mm filtering
(Total point count: 42 947 892)
|Top view||Top view|
|Side view (5 meters away)||Side view (5 meters away)|
|Project size: 0.55 GB||Project size: 1.07 GB|
Some time is necessary to use a project clipping box (project area boundaries) to eliminate noise points or create an Undet project only in the required location.
In “Clip Box Settings” you need to insert your project MIN – MAX meanings for each coordinate.
|Undet project created without project clipping box (all data)||
Undet project created without project
clipping box (all data).
|Silver box is clipping area to create Undet project.||Undet project created using project clipping box|
To import not structured TXT point cloud data files, you can manually set file data format. Clicking in format column on the selected file “Add…”
In the next dialog, you will need to select data file: separators and column fields for column values: X, Y, Z, R, G, B, and intensity.
To create Undet project you need triple (3x) size on your HARD DRIVE according to your scan data file size.
As an example: scan data files size (20 pcs. *. e57 files 10GB), so you will need 30GB free disk space.
If you have enough disk space for project creation, please disable the “check disk space” option and the indexing process will be much faster.
Otherwise, with enabled “check disk space” function, software during the indexing process will inform you that you don’t have enough disk space and you will be able to free up disk space and continue the indexing process. Please note that this strongly slows down the indexing process.