ATIS.cloud
IndustryUpdated on April 18, 2026

Best Practices for Creating 3D Point Clouds

A detailed, precise 3D model starts with a clean point cloud. Here are the key decisions to get right before you even open the scanner, from coverage planning to registration method.

Estimated read: 5 min

Project managers, designers, construction crews and engineers all rely on point clouds today, the possibilities keep expanding as the technology matures. Getting a detailed, precise 3D model out of a scanning campaign requires more than just pointing the scanner at the site. This article walks through the key decisions to get right, and the trade-offs they imply.

What registration really is (and why it's the hard part)

A detailed 3D model is almost always built from several scans of the same area that need to be aligned into a single coherent cloud. This alignment is called “registration”. It has historically been the bottleneck of point cloud workflows: registration quality directly drives the precision of everything downstream.

When GNSS can help (and when it can't)

Global Navigation Satellite System data (GPS/GNSS) can align scans using the scanner's geolocation when the scan happened. It works well in open sites. It breaks in indoor environments, narrow urban canyons, forests, or anywhere the sky is blocked. For those sites, you need another registration method.

Target-based vs. targetless registration

Target-based registration

Targets are artificial, easily-recognized markers placed in the environment before scanning. The software finds them in each scan and uses them as anchor points. You need at least three targets visible in each pair of overlapping scans. Placement has to be planned: too few and you can't register; too many and your campaign slows to a crawl. Every site adds its own constraints, access, obstructions, safety, and placing targets always costs time on the ground.

Targetless registration

Targetless (a.k.a. cloud-to-cloud) registration uses the geometry already present in the scans, corners, edges, walls, to align them. You save time on site but you push more work into the office. Traditional targetless software requires up to 60% overlap between scans and manual validation of each pair; distortions or inaccuracies in a single scan can ripple through the whole project.

« ATIS.cloud allowed us to reduce delivery time by 2 hours per project. Our clients view scans immediately. »
James · Licensed Surveyor · Horizon Surveying

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Practical tips for a clean point cloud

  • Plan your scan positions before you arrive on site, don't improvise overlap
  • Aim for 30–40% overlap between adjacent scans when using targetless registration
  • Use targets in featureless environments (empty rooms, corridors, tunnels)
  • Keep the scanner stable: a moved tripod mid-scan ruins the registration
  • Capture color and intensity data whenever the project allows, richer metadata downstream
  • Document your scan plan (positions, targets, dates) for the BIM team to trace back issues

Share the cloud early, not at the end

One of the biggest gains in the last years has come from platforms like ATIS.cloud that let you share the point cloud with the whole team the minute it's registered. No more waiting two weeks for a final deliverable to surface a problem, clients, BIM managers and on-site engineers can review the cloud directly in their browser and flag issues immediately.

A clean point cloud isn't produced on site alone, it's the result of good planning, the right registration method for the environment, and a sharing workflow that pulls the whole team in early. Skip any of those and you pay for it in reprojects.

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