Point Cloud

The filtering mechanisms available for selection on the Survey tab, in the Point Cloud group, enable point cloud data to be imported and processed more efficiently.

• Click Point Cloud to Solid to map underground workings by converting 3D laser scan point clouds (LIDAR) to wireframes. The function provides an advanced approach to point cloud modelling which uses a “shrink wrap” algorithm to generate an outer shell.

• Click Ground to use Ground-based filtering to separate a LIDAR point cloud into ground and non-ground measurements.

• Due to measurement errors, imported point cloud data may contain a large number of shadow points, or noise, which can affect the clarity of 3D surfaces or solids extrapolated from the data.

  Click Noise to use Noise-based filtering to apply a filter mechanism to reduce the noise in an input point cloud data file.

• Downsampling may be used to simplify a dense point cloud so that processing is more efficient and interpretation clearer.

  Click Downsample to apply a filter mechanism to resample the points in an input point cloud data file.

• Click Generate Attributes to generate dimension attributes for point cloud data.