REALITY CAPTURE KNOWLEDGE · POINT CLOUDS
Higher point density is not automatically better.
There are projects where dense point cloud data is important. If the objective is to create a detailed mesh, for example, the additional geometric information can be valuable.
But if the required measurements, geometry or documentation can be reliably extracted from a lower-density point cloud, additional points may simply create a larger dataset.
That affects storage, transfer, processing performance and the ability of downstream systems to work efficiently with the data.
The right point density is therefore always project-dependent.
More points only add value when the project actually needs them.
SEE IT IN PRACTICE
During a digital cemetery mapping project, the processed datasets contained more data than the target platform could efficiently handle. The point clouds were downsampled while preserving the geometry required for the final application.
ABOUT THIS KNOWLEDGE SERIES
Reality Capture Knowledge is where I share short, practical answers to questions that come up across reality capture, point cloud processing and geospatial workflows.
The answers are based on more than 15 years of hands-on experience working with spatial data, field acquisition and point cloud processing.
Roland Kriston
Independent Reality Capture & Geospatial Specialist