ATIS.cloud
IndustryUpdated on May 14, 2026

What Is a Point Cloud? Guide 2026 (LiDAR, Formats, Uses)

What a point cloud is, how LiDAR and photogrammetry create them, common formats (E57, LAS, LAZ, RCS, RCP, LGSx), and what professionals do with them.

Estimated read: 9 min

A point cloud is, at its simplest, a list of XYZ coordinates that together describe the surface of an object or a building. The list can be a few thousand points (a scanned chair) or several billion (a whole industrial plant). What you do with that list is where it gets interesting: you can measure, you can compare against a model, you can extract a digital twin, you can spot a 5 mm sag on a structural beam.

Definition: a point cloud, technically

A point cloud is a discrete set of data points in space. Each point position has a set of Cartesian coordinates (X, Y, Z), and may carry several extra attributes depending on the scanner.

  • X, Y, Z: the mandatory Cartesian coordinates that locate the point in 3D space.
  • RGB color: captured when the scanner embeds a camera. Produces a realistic-looking cloud.
  • Surface normals: the direction the surface faces at that point, useful for meshing and lighting.
  • Intensity: how strongly the laser pulse returned. Reveals materials (concrete, metal, vegetation).
  • Timestamp: when the point was captured, key for mobile mapping and 4D analysis.
  • Classification: a label (ground, vegetation, building) added in post-processing, common in outdoor LiDAR.
1 pointX, Y, Z (required)RGB colorNormalsIntensityTimestampClassification+ customMultiply by millions or billions = a point cloud
Anatomy of a single point. The cloud is just this, multiplied billions of times.

Two notes for newcomers. First: a point cloud is not the same thing as a 3D model. A model has surfaces, edges, semantics. A point cloud is just the dots. You can convert dots to surfaces ("meshing") or compare dots to a designed model ("scan vs BIM", called "as-built"), but the raw cloud is geometry without semantics.

Heads up: two unrelated meanings

Do not confuse the 3D point cloud (LiDAR, photogrammetry, AEC, surveying, industry) with the 2D scatter plot used in statistics, which is also called nuage de points in French. Same name, completely different topic. This article only covers the 3D one.

How point clouds are created

LiDARlaser pulsesPhotogrammetryoverlapping photosDepth camerasphones, RealSense, KinectPoint cloudXYZ + attributes
Three families of sensors, one common output format.

1. LiDAR (laser scanning)

A LiDAR scanner emits a laser beam, measures how long the beam takes to return, computes the distance, and records a point. Repeat that millions of times per second, sweeping the field of view, and you get a point cloud. Static terrestrial scanners (used in surveying and AEC) deliver millimeter accuracy. Mobile mapping scanners (mounted on a backpack, a vehicle, a drone, an autonomous robot) trade some accuracy for speed and coverage.

Many scanner manufacturers share the professional market, each with its own range, native file format and workflow:

  • FARO, Leica (Hexagon), NavVis, Riegl
  • Trimble, Viametris, Matterport, etc.
  • A platform that handles all of them natively (no manual format wrangling) saves real time on mixed-fleet operations. ATIS.cloud supports every scanner brand out of the box.

2. Photogrammetry

Take many overlapping photos of a scene from different angles, run them through photogrammetry software (Agisoft Metashape, RealityCapture, ContextCapture, Pix4D, OpenDroneMap), and the software triangulates 3D points from the images. The result is a colored point cloud, sometimes denser than LiDAR, sometimes less accurate, depending on lighting and surface texture. Drone photogrammetry is now the dominant method for large outdoor sites (quarries, agriculture, archaeology, infrastructure).

3. Other sources (depth cameras, smartphones, simulation)

Depth cameras (Intel RealSense, Microsoft Kinect generations, Apple's iPhone Pro / iPad Pro LiDAR sensor), structured-light scanners and even simulated point clouds (in Unity, Unreal, robotics training) all produce data of the same family. The geometry conventions are the same; the accuracy and the file size differ massively.

MethodTypical accuracyBest forWatch out for
Terrestrial LiDARMillimeterAEC, surveying, industry, heritageStatic, slower on large outdoor sites
Mobile LiDAR (backpack, vehicle, drone)CentimeterLarge coverage, infrastructure, mappingLower accuracy than terrestrial
Drone photogrammetryCentimeterQuarries, agriculture, archaeology, large outdoorLighting and texture dependent
Depth cameras / smartphone LiDARCentimeter to decimeterIndoor scenes, prototyping, small objectsNot survey-grade
We work with five scanner brands across our projects. Having one platform that reads all of them natively, without conversion scripts, is a productivity gain we hadn't anticipated, and it's now one of our biggest daily time-savers.
Sébastien · Geometre-topographe, cabinet independant

Common point cloud file formats

Pick the right format and you spend your time on the project, not on conversion. Pick the wrong one and you ship the wrong file to your client. Here are the formats you will encounter, what they are good for, and whether they are open or proprietary.

FormatOpen / proprietaryTypical use
E57Open (ASTM E2807)Default interchange across the industry
LASOpen (ASPRS)LiDAR reference, outdoor and aerial
LAZOpen (compressed LAS)Same as LAS, 80-90% lighter to ship
RCS / RCPProprietary (Autodesk Recap)Autodesk workflows. ATIS.cloud reads/writes them without an Autodesk license
LGSxProprietary (Leica Hexagon)Hexagon ecosystem (Cyclone, etc.)
PLY, OBJ, PCD, PTS, XYZOpen (legacy / research)Still encountered, less standard in production AEC
  • E57: open ASTM standard (E2807). The default interchange format across the industry; supported by most scanners and most software. Good first choice when you do not control downstream tooling.
  • LAS: open standard from the American Society for Photogrammetry and Remote Sensing (ASPRS). The reference format for LiDAR data, particularly outdoor / aerial.
  • LAZ: a compressed LAS (typically 80 to 90 percent smaller). Same content, much lighter to ship. Open and widely supported.
  • RCS / RCP: native Autodesk Recap formats. Read and written natively by ATIS.cloud without an Autodesk license required, which is unusual on the market.
  • LGSx: proprietary Leica Hexagon format. The Hexagon ecosystem is migrating progressively from "Leica" to the "Hexagon" naming.
  • PLY, OBJ, PCD, PTS, XYZ: legacy or research formats, still encountered, less standard in production AEC workflows.
« Test ATIS.cloud with your own scan: E57, LAS, LAZ, RCS, RCP or LGSx up to 1 TB. 14-day free trial, no credit card. »

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What professionals do with a point cloud

Different industries reach for the same point cloud for very different reasons. Same dots, different deliverables. Six sectors account for nearly all professional usage:

IndustryWhat they do with the cloudTypical deliverable
Surveying & topographyDocument existing site, compute volumesAs-found drawings, DTM, DSM, stockpile volumes
AEC & BIMScan vs BIM (called "as-built"), scan-to-BIMAs-built model, clash reports, deviation maps
IndustryDocument plant, monitor deformation, plan retrofitsDigital twin, VR walkthroughs, retrofit drawings
Heritage & archaeologyArchive monuments, plan restorationsMillimeter archive, restoration plans, digital exhibits
InfrastructureInspect bridges, tunnels, highways, railwaysClearance reports, defect tracking, maintenance plans
Forestry & agricultureEstimate biomass, count plants, analyze terrainBiomass reports, yield maps, terrain models
  • Surveying and topography: deliver as-found drawings, volumes (stockpiles, excavations), DTM and DSM
  • AEC and BIM: scan an existing building, compare scan vs BIM model (called "as-built"), feed scan-to-BIM workflows
  • Industry: document a plant, monitor structural deformation, plan retrofits, train operators in VR / digital twin environments
  • Heritage and archaeology: archive a monument with millimeter accuracy, plan a restoration, build digital exhibits
  • Infrastructure: bridge inspection, highway maintenance, railway clearance checks, tunnel monitoring
  • Forestry and agriculture: forest biomass estimation from aerial LiDAR, plant counts, terrain analysis
  • Drone and surveying SaaS: serve scans to clients via secure link, with measurement and annotation in the browser

How to view and share a point cloud

Once a scan is captured, two questions decide what tooling fits: how big is the file, and who needs to see it.

  • Small to medium files, desktop, internal use: CloudCompare (open source) or Autodesk Recap (commercial). Install, open, work.
  • Large files or external sharing: a managed SaaS that streams the cloud in the browser. No install for your client, no oversize email, no expired WeTransfer link.
  • Mixed-fleet operations: prefer a platform that reads all common formats natively (E57, LAS, LAZ, RCS, RCP, LGSx), so you do not maintain conversion pipelines.

ATIS.cloud is the platform we build for that exact use case: scans up to 1 TB per file (5 TB of total workspace), native support for every scanner brand, formats E57, LAS, LAZ, RCS, RCP, LGSx, secure link sharing, sovereign hosting in 22+ countries, 14-day free trial without credit card.

« I share my scan and the model with the contractor in the same browser session. No more sending 4 GB files by WeTransfer. »
Marc · BIM Manager · firme d'architecture indépendante

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A point cloud is a list of XYZ coordinates that describe the surface of an object or a building, captured by LiDAR or photogrammetry. The common professional formats are E57, LAS, LAZ, RCS, RCP and LGSx. Pros use point clouds in surveying, AEC, industry, heritage, infrastructure and forestry. To view and share with clients in a browser, a managed SaaS like ATIS.cloud handles up to 1 TB per file across every native scanner brand, with a 14-day free trial.

Frequently asked questions

A point cloud is a list of XYZ coordinates (sometimes with color, normals or classification) that describes the surface of an object or a building, typically captured by a 3D laser scanner (LiDAR) or by photogrammetry from a series of overlapping photos.

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