When BOND Building Construction was awarded a statewide infrastructure contract to scan and model hundreds of facilities, they knew the scope would test every part of their workflow.
The job was large and complicated. Over 470 buildings were in scope, from airport terminals and cruise ship docks to warehouses and administrative spaces. The client, a major transportation authority in Massachusetts, expected georeferenced models and point clouds that would feed directly into both GIS and BIM systems. The timeline: five years.
For Sean Doyle, Director of Integrated Design at BOND, the deliverables weren’t unfamiliar. But the scale and time pressure meant they would need to rethink how those deliverables were produced.
Historically, BOND had relied on terrestrial laser scanning (TLS). It was accurate and familiar, especially for above-ceiling infrastructure work, which forms a major part of their portfolio. SLAM-based laser scanning, by contrast, had always seemed like a compromise.
“We just really weren’t yet bought in on SLAM scanning,” Sean admitted. “We were late adopters.”
That changed in 2022. By then, BOND had already purchased its first NavVis VLX and begun using it on smaller projects, building confidence internally. The team was convinced. The question was whether their client—who had also historically been skeptical of SLAM—would allow the technology to be used at scale. A million-square-foot airport terminal (≈92,900 m²) became the proving ground.
Starting with the Hardest Site
The terminal was one of the most difficult buildings in the client’s portfolio. Spread across three floors and shaped like a horseshoe, it housed seven airlines, each with its own leased spaces, access restrictions, and points of contact. Even basic coordination required extensive planning.
Before any scanning began, BOND spent seven full business days walking the entire terminal with key stakeholders: airline reps, TSA officials, security staff, facilities managers. They visited every accessible room. They flagged issues with keycards and access control. In some cases, they even helped the owner discover which rooms they no longer had access to themselves.
“We were in spaces no traveler will ever see,” Sean said. “Baggage tunnels, inspection rooms, mechanical spaces. It wasn’t glamorous, but it meant we wouldn’t waste time doubling back later.”
By the end of the walkthrough, they had a room-by-room plan and over 40 access contacts logged. The site was ready.
Methodology: Survey Control Meets Mobile Mapping
BOND took a hybrid approach. First, a professional surveyor ran a total station loop around the perimeter of the terminal, connecting into the owner’s established monument network. Then, BOND used terrestrial scanners to capture circulation corridors and stairwells—just enough to create checkerboard targets across the terminal. Roughly every 35 to 40 feet (~10.7–12.2 meters), they installed a target that could be picked up during SLAM runs.
That groundwork formed the control spine. The rest of the scanning was handled by two NavVis VLX 3 units and one NavVis MLX unit.
“We maybe only scanned 100,000 square feet (~9,290 m²) of the million with TLS,” Sean said. “The rest we did with SLAM.”
The checkerboards gave the SLAM data anchor points across all three levels. And because they ran total station work in parallel with the scanning effort, there was no delay.
“It allowed us to blaze a trail through the terminal,” Sean said. “And we could come back later if needed, without compromising accuracy.”
| Metric | Value |
|---|---|
| Total area scanned | 1,000,000 sq. ft. (~92,900 m²) |
| Primary scanning duration | 5 working days |
| Total field time (incl. control) | 12 days |
| Scanning schedule | 3 nights per week (Monday–Wednesday) |
| Data volume (point cloud) | 250 GB |
| Expected volume with TLS | ~1 TB (colorized static scans) |
| Checkerboard target spacing | Every 35–40 ft (~10.7–12.2 m) |
| Pre-scan walkthroughs | 7 business days |
| Stakeholders coordinated | 40+ (airlines, TSA, vendors, facilities, security) |
| On-site scanning team | 4 people |
| Remote modeling team | 30+ people across 8 U.S. states |
| Scan data registration time | 2 days |
| NavVis VLX datasets cleaned | 78 datasets, cleaned in 1 day |
| Client cost savings | ~20% compared to TLS-based approach |
| Workflow speed increase | 3× faster than legacy methods (12 weeks → 4 weeks) |
| Point cloud accuracy delivered | ¼ inch (~6 mm) |
Speed and Scale
The actual scanning took five working days. By the end of the first week, they had captured 95% of the terminal. A few small rooms had to be revisited, but the core of the building was done. The team worked only three nights per week (Monday to Wednesday), and only four staff members needed field access.
The remaining 30 team members worked remotely, modeling from NavVis IVION. They were spread across eight states and three companies. Some never set foot in the building at all.
“They’ll never step on site,” Sean said. “But they’re modeling it just fine.”
Data was processed in two days. Once checkerboards were extracted from the TLS scans and matched with SLAM control, the data was grouped and uploaded. Total data volume: 250 GB. With colorized TLS, the same project would have produced over 1 TB.
“We turned 12 weeks into 4,” Sean said. And, referring to the title of the webinar: “Maybe it should be triple the efficiency, not double.”
Automation Replaces Cleanup
In parallel, Sean compared the labor impact to a concurrent project: a university building scanned with TLS. That job required over 3,000 scans, each of which needed to be cleaned manually. People, license plates, reflections—everything had to be deleted.
“It’s going to take a month,” Sean said. “Just for cleanup.”
By contrast, the airport project used NavVis IVION’s automated object removal and cleanup tools. In one day, the team processed and cleaned all 78 datasets.
A Different Kind of Cost Model
Processing cost was passed to the client—roughly one to two cents per square foot (~€0.11–0.22/m²), depending on the project. The client raised no objections.
“For the same project, side by side, there’s about a 20% savings for the owner,” Sean said. “And we’re still making money.”
That tradeoff—shifting labor cost to automation—also improved scalability. The scanning unit was in the field six days a week, not waiting on cleanup. More projects could be scheduled sooner. Less time was spent sitting at a desk, stitching together scans.
“The project wouldn’t exist if we couldn’t deliver it in a cost-effective way,” Sean said. “I’d rather pay for processing than pay someone $80 an hour to clean up TLS data.”
From Opposed to Embedded
There was one final irony. Several years earlier, Sean had helped co-write the client’s scanning standards. Those standards explicitly rejected SLAM as a viable tool.
“We wrote the rules that said not to use SLAM,” he said. “Now we’re rewriting them.”
What changed wasn’t just the technology. It was the planning, the trust in control workflows, and the proof that SLAM could handle complexity.
NavVis didn’t replace rigor. It gave BOND more room to apply it where it mattered, at a much larger scale.
To watch the webinar with NavVis and BOND Construction that inspired this blog, visit this page:
"Faster Scans, Lower Cost: How to Double your Efficiency with NavVis Solutions"
