Evaluation of data

acquisition techniques

and workflows for Scan

to BIM

Maarten Bassier

Scan to BIM

• AEC industry buildings

• Mid-to-large scale data sets

• LOD 300

• LOA 30

Image from http://www.severnpartnership.com/

Traditional Workflow

Images from http://www.quantapoint.com/, http://www.laserscan-3d.com/,

http://nl.kubit-software.com/

Workflow optimization

• Terrestrial laser scanner measurements

• High overlap

• Cloud to cloud registration

• Network optimization

• Loop closure

• GPS for geolocation

Mid-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

• 70x40x4m

• 97 scans

• 5-10 m/scan

• 4h acquisition

• 97 manual constraints

• 1500 auto constraints

• 7h post-processing

Mid-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

• 33 targets

• ±2mm

• < 1day

Acquisition time [h] Post processing [h] Total

[h]

Traditional workflow Point cloud 4 7 11

Total station 4 3 7

Efficiency 50% 30% 39%

Mid-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

X Y Z

% within specification

(1.5cm) 100% 100% 100%

Biggest error [m] 0,0068 0,0079 0,0120

RMSE [m] 0,0025 0,0028 0,0051

Mid-Scale Test Case

4m

Dataset from http://www.3dgeosolutions.nl/

Mid-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

0.004

0.002

0.002

0.005

0.001 0.011

0.003

0.004

0.006

0.006

0.005

0.003

0.005

0.005

0.005

0.006

0.001

0.001 0.001

0.003

0.002

0.005 0.002

0.012 0.003 0.004

0.003

0.0

0.0

0.004

• Deviations [m]

Mid-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

150m ≈ 22,500m²

Large-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

• 250x100x10m

• 422 scans

• 16h acquisition

• 421 manual constraints

• 4900 auto constraints

• 30h post-processing

Large-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

• 146 targets

• ±2mm

• < 1day

Acquisition time [h] Post processing [h] Total

[h]

Traditional workflow Point cloud 16 30 46

Total station 16 5 21

GPS 3 1 4

Efficiency 46% 14% 30%

Large-Scale Test Case

X Y Z

% within specification

(1.5cm) 100% 100% 64%

Biggest error [m] 0,0117 0,0107 0,0371

RMSE [m] 0,0052 0,0040 0,0170

0.037 0.011

0.012

0.013

0.010

0.003

0.017

0.020

0.015 0.019

0.017

0.013

Dataset from http://www.3dgeosolutions.nl/

0.007

0.008

• Deviations [m]

Large-Scale Test Case

Dataset from http://www.3dgeosolutions.nl/

200m ≈ 40,000m²

Prediction models

Dataset from http://www.3dgeosolutions.nl/

250m

70m

GPS integration

Dataset from http://www.3dgeosolutions.nl/

X Y Z

% within specification

(1.5cm) 100% 100% 100%

Biggest error [m] 0,0140 0,0126 0,0149

RMSE [m] 0,0067 0,0051 0,0071

• 6 GPS targets • ±1,5cm

Conclusions

• Terrestrial laserscanning is the best solution for mid-to-

large scale Scan to BIM projects

• Cloud to cloud registration and GPS measurements

can acquire project deliverables without total station

measurements

• Depending on data variance, predictions can be made

about project accuracy