LIS Thinning - point cloud thinning and homogenization
This package contains tools for point cloud thinning, including 2D and 3D blockthinning, TIN based thinning, thinning based on surface roughness, and tools providing thinning options for virtual point cloud datasets (massive data).
Tool: 2D Block Thinning (PC)
| Features |
|---|
| • thinning of a point cloud by 2D block filtering (from all points contained within a 2D grid cell only one is kept) |
| • filter methods: lowest, highest, nearest (cell center), mean, median, min(attribute), max(attribute) |
| Application |
|---|
| • point cloud thinning / data reduction |
| • point cloud thinning based on attribute value, e.g., point with highest intensity value is kept |
Tool: 2D Block Thinning (SPCVF)
| Features |
|---|
| • thinning of a point cloud by 2D block filtering (from all points contained within a 2D grid cell only one is kept) |
| • filter methods: lowest, highest, nearest (cell center), mean, median, min(attribute), max(attribute) |
| • input: subset extracted from virtual point cloud data set (massive data) based on provided AOI |
| • possibilty to constrain query to a certain attribute range, e.g., ground points |
| Application |
|---|
| • point cloud thinning / data reduction |
| • point cloud thinning based on attribute value, e.g., point with highest intensity value is kept |
| • spatial subsetting from virtual point cloud data set (massive data) with on-the-fly thinning |
Tool: 2D Block Thinning (SPCVF) [interactive]
| Features |
|---|
| • thinning of a point cloud by 2D block filtering (from all points contained within a 2D grid cell only one is kept) |
| • filter methods: lowest, highest, nearest (cell center), mean, median, min(attribute), max(attribute) |
| • input: subset extracted from virtual point cloud data set (massive data), interactive selection of AOI in a Map View |
| • possibilty to constrain query to a certain attribute range, e.g., ground points |
| Application |
|---|
| • point cloud thinning / data reduction |
| • point cloud thinning based on attribute value, e.g., point with highest intensity value is kept |
| • spatial subsetting from virtual point cloud data set (massive data) with on-the-fly thinning |
Tool: 2D Delaunay Thinning (PC)
| Features |
|---|
| • thinning is controlled by a deviation tolerance describing the elevation difference allowed between the 2D triangulation of the thinned point cloud and that of the original point cloud |
| • points with a high curvature, e.g., along breaklines, can be kept, optional |
| • output of the final (thinned) TIN as 3D shapefile, optional |
| Application |
|---|
| • point cloud thinning / data reduction |
| • TIN generation (3D shapefile) |
| • detection of (terrain) keypoints |
Tool: 3D Block Thinning (PC)
| Features |
|---|
| • thinning of a point cloud by 3D block filtering (from all points contained within a 3D voxel only one is kept) |
| • filter methods: lowest, highest, nearest (voxel center), mean, median, z-slice mean, min(attribute), max(attribute), center |
| Application |
|---|
| • point cloud thinning / data reduction |
| • point cloud thinning based on attribute value, e.g., point with highest intensity value is kept |
| • homogenization of point density |
Tool: 3D Block Thinning (SPCVF)
| Features |
|---|
| • thinning of a point cloud by 3D block filtering (from all points contained within a 3D voxel only one is kept) |
| • filter methods: lowest, highest, nearest (voxel center), mean, median, z-slice mean, min(attribute), max(attribute), center |
| • input: subset extracted from virtual point cloud data set (massive data) based on provided AOI |
| • possibilty to constrain query to certain attribute range, e.g., ground points |
| Application |
|---|
| • point cloud thinning / data reduction |
| • point cloud thinning based on attribute value, e.g., point with highest intensity value is kept |
| • spatial subsetting from virtual point cloud data set (massive data) with on-the-fly thinning |
| • homogenization of point density |
Tool: 3D Block Thinning (SPCVF) [interactive]
| Features |
|---|
| • thinning of a point cloud by 3D block filtering (from all points contained within a 3D voxel only one is kept) |
| • filter methods: lowest, highest, nearest (voxel center), mean, median, z-slice mean, min(attribute), max(attribute), center |
| • input: subset extracted from virtual point cloud data set (massive data), interactive selection of AOI in a Map View |
| • possibilty to constrain query to certain attribute range, e.g., ground points |
| Application |
|---|
| • point cloud thinning / data reduction |
| • point cloud thinning based on attribute value, e.g., point with highest intensity value is kept |
| • spatial subsetting from virtual point cloud data set (massive data) with on-the-fly thinning |
| • homogenization of point density |
Tool: Thinning by Surface Roughness (PC)
| Features |
|---|
| • thinning of a point cloud (e.g., a bare earth model) in consideration of surface roughness |
| • areas with a low surface roughness will be thinned out more rigorous than areas with a high roughness |
| • additional output: final (thinned) TIN as 3D shapefile |
| • TIN can be constrained to data, optional |
| • detection of (terrain) breaks by normal vector difference, optional |
| Application |
|---|
| • point cloud thinning / data reduction |
| • TIN generation (3D shapefile) |
| • detection of (terrain) keypoints |