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Key Points
What Is a Point Cloud?
A point cloud is a collection of spatially located points that represents sampled visible surfaces. Each point carries XYZ coordinates and may also carry intensity, color or scan position information. The cloud becomes useful when its registration, coordinate basis, coverage, organization and export format match the downstream project workflow.
Our Approach
How we help your team
Your point cloud should be easy to locate, open and use in the software your team already works with. We help you define the coverage, coordinate system and file format before preparing the delivery.
We review registration and coverage, preserve the agreed coordinates and organize the data for practical use. Your delivery includes the native or exchange files agreed with your team for measurement, coordination, CAD or BIM work.
Part 1 of 6
What information a point can contain
At minimum, a point locates a sample in three-dimensional space. Depending on the sensor and file format, it can also carry return intensity, RGB color values, a timestamp or information that preserves which scan station produced it. Structured scan data can retain the rows, columns, poses and panoramic relationship associated with each station; unified exports may combine the samples into a simpler whole.
That distinction matters. Some review tools depend on station structure and imagery, while many CAD and BIM workflows need a performant indexed cloud. The delivery conversation should cover what information must survive the handoff, not only the filename extension.
Part 2 of 6
Density, spacing and coverage
Point spacing normally increases with distance from a terrestrial scanner because the angular sampling spreads over a larger surface. A resolution setting that is sufficient at ten meters may not capture the same small feature at fifty meters. Surface angle and reflectivity also influence how cleanly returns describe an edge or plane.
Coverage is different from density. A surface can be sampled densely from one side but absent behind an obstruction. For design work, complete views of the relevant faces and transitions often matter more than maximizing the number of points everywhere.
Part 3 of 6
Why registration and coordinates matter
A multi-station project is only coherent after the scans are registered. Local projects may use a convenient project coordinate system; survey-controlled projects may relate the cloud to established control or a published grid. Units, axis orientation and large coordinates must be managed deliberately before the data enters design software.
A visually aligned cloud can still contain local registration weakness or a coordinate mismatch. Handoffs should document the coordinate basis and include identifiable checkpoints so the receiving team can verify position after import.
Part 4 of 6
Common point cloud formats
E57 is a documented interchange format capable of storing 3D point data, attributes and imagery. Autodesk ReCap can import E57, FLS, FWS, LSPROJ and other formats and can export E57, PTS and RCP/RCS. RCP is a project/index file that references RCS scan data for Autodesk workflows.
A format conversion does not improve registration and can remove information if the chosen export does not preserve scan structure, imagery, clips or coordinate behavior. The sender and recipient should test the exact application versions and a representative file before a large delivery.
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| Format | Typical use | Question to confirm |
|---|---|---|
| E57 | Vendor-neutral structured or unstructured exchange | Will station poses, imagery and intended coordinate transforms be preserved? |
| RCP/RCS | Indexed Autodesk ReCap, AutoCAD and Revit workflows | Which origin and positioning method will the design model use? |
| FLS/FWS/LSPROJ | FARO native scan and project workflows | Does the recipient need native scans, the project database or both? |
| LAS/LAZ | Survey, geospatial and classification workflows | Are units, classification and coordinate reference metadata documented? |
Part 5 of 6
How project teams use point clouds
Designers can reference a cloud directly to inspect existing geometry, take qualified measurements, develop plans and sections or model selected elements. Construction and industrial teams can compare captured conditions, plan access, coordinate installations and preserve a time-specific record within the limits of the scope.
Performance also matters. Large projects may need spatial segmentation, regions, decimation for a particular viewer or multiple delivery packages. An organized cloud with a clear readme is generally more useful than one enormous file with no context.
Part 6 of 6
What a point cloud does not prove
A point cloud does not automatically identify materials, hidden construction, ownership, code compliance or design intent. Color is photographic information affected by lighting and capture settings; it is not a calibrated material test. Missing points can mean occlusion, range, reflectivity, filtering or an uncaptured area.
Treat the cloud as a measured spatial reference with defined limits. Document when it was captured, which areas were included, how it was registered and what acceptance checks were performed.
Ask how the cloud was registered, checked, organized, referenced and exported. Those details tell you whether the delivered file will support your work.