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Shareable High Resolution 3D Point Cloud Classification
SHR3D classifies a 3D point cloud to generate simple geospatial products, including: a Digital Surface Model (DSM); a Digital Terrain Model (DTM); a classification image labeling ground, buildings, and trees; and a simplified building outlines vector product.
./shr3d <Input File(LAS|TIF)> DH=<Horizontal uncertainty(m)> DZ=<Vertical uncertainty(m)> AGL=<Min building height(m)> AREA=<Min building area(m^2)>
./shr3d shr3dMe.las DH=0.5 DZ=0.5 AGL=2 AREA=50
This will produce multiple files as a result:
- Raster files (*.tif):
- Classification image- 'Colored' by classification for each pixel: buildings, ground, and trees
- Building image- Binary mask of all detected buildings
- DSM- Digital surface model (reflective surface)
- DTM- Digital terrain model (bare earth, or ground)
- Vector files (shapefiles: *.shp, *.prj, *.shx, *.dbf):
- Building outlines- Simplified polygons of detected building perimeters
Align 3D Point Cloud Registration Tool
ALIGN3D estimates and applies a transform to align 3D point clouds. This algorithm was developed for use with airborne lidar, multiple view satellite imagery, and synthetic aperture radar derived point clouds.
./align3d <Reference point cloud(LAS)> <Target point cloud(LAS)> maxdz=<Maximum local z difference(m)> gsd=<Ground sample distance(m)> maxt=<Maximum XY translation for search(m)>
./align-3d reference.las target.las maxt=10.0 gsd=1.0
This will produce multiple output files:
- Aligned.las- A point cloud representation of the target, aligned to the reference
- Aligned.tif- A DSM of the target, aligned to the reference
- Offsets.txt- A list of the xyz offsets to translate the target to align with the reference