Command line example
Posted: Sun Nov 26, 2023 7:47 pm
Hi,
I'm currently trying to learn the command line function having always used the GUI. Can anyone offer an example workflow? I'm trying all manner of commands using the example wiki as well as some AI assistance but its not going too well and i'm not very good with command line stuff, i much prefer visual interface but i need to speed my work up due to processing large quantities of data to obtain accurate canopy height models.
1 Load las files - around 20 1km2
2 Merge files
3 Set scalar to classification
4 Split cloud (integer values)
5 Clone classes 2, 9 and 11
6 Merge 2, 9 and 11 clones
7 Rasturise cloud at .5 and Krig
8 Export Cloud and Mesh to DB tree
9 Normalise both (Mesh - per-vertex and Raster - auto octree with +Z orientation)
10 Compute cloud/mesh distance for classes 3, 4 and 5 in the split cloud data (low, med and high vegetation)
11 Change and export the display ranges for 3, 4 and 5 (0.05-0.15/0.15-2/2->)
12 Merge the new classes from each original class. For example class 3, 4 and 5 with ranges of 0.05-0.15 are all merged into a new class 3 for low vegetation. The same for the other ranges into a new class 4 (0.15-2) and a new class 5 (2>).
13 Reclassify each new class using the segment tool and set class tool.
14 Move new classes 3,4 and 5 into split cloud group within the DB tree. Delete the old 3, 4 and 5.
Then export/save rasters for each class from 3-17 as well as the raster DTM cloud created from the kriging process with the rasturise tool.
15 Save DB tree as bin file for merged area.
Any help would be greatly appreciated
D
I'm currently trying to learn the command line function having always used the GUI. Can anyone offer an example workflow? I'm trying all manner of commands using the example wiki as well as some AI assistance but its not going too well and i'm not very good with command line stuff, i much prefer visual interface but i need to speed my work up due to processing large quantities of data to obtain accurate canopy height models.
1 Load las files - around 20 1km2
2 Merge files
3 Set scalar to classification
4 Split cloud (integer values)
5 Clone classes 2, 9 and 11
6 Merge 2, 9 and 11 clones
7 Rasturise cloud at .5 and Krig
8 Export Cloud and Mesh to DB tree
9 Normalise both (Mesh - per-vertex and Raster - auto octree with +Z orientation)
10 Compute cloud/mesh distance for classes 3, 4 and 5 in the split cloud data (low, med and high vegetation)
11 Change and export the display ranges for 3, 4 and 5 (0.05-0.15/0.15-2/2->)
12 Merge the new classes from each original class. For example class 3, 4 and 5 with ranges of 0.05-0.15 are all merged into a new class 3 for low vegetation. The same for the other ranges into a new class 4 (0.15-2) and a new class 5 (2>).
13 Reclassify each new class using the segment tool and set class tool.
14 Move new classes 3,4 and 5 into split cloud group within the DB tree. Delete the old 3, 4 and 5.
Then export/save rasters for each class from 3-17 as well as the raster DTM cloud created from the kriging process with the rasturise tool.
15 Save DB tree as bin file for merged area.
Any help would be greatly appreciated
D