Point clouds of Constructie bridge on Westlandseweg, Delft, The Netherlands

doi: 10.4121/13626188.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/13626188
Datacite citation style:
Linh Truong; Roderik Lindenbergh; Qian Bai; Harm Kathman; Owen O'Driscoll (2021): Point clouds of Constructie bridge on Westlandseweg, Delft, The Netherlands. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/13626188.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
Delft University of Technology logo
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geolocation
Westlandseweg, Delft, Zuid-Holland, The Netherlands
lat (N): 52.005037
lon (E): 4.359427
view on openstreetmap
licence
cc-by-nc.png logo CC BY-NC 4.0

Point clouds of Constructie bridge on Westlandseweg in Delft was acquired for the project “Laser Scanning for Automatic Bridge Assessment” or called “BridgeScan” funded through H2020 Marie Curie IF and for a big assignment of a course “3D Surveying of Civil and Offshore Infrastructure” of a Master program at TU Delft Dept. Geoscience and Remote sensing”. The Constructie bridge is a concrete bridge with mix-vehicle and tram bridge with one span over a channel. The data points of the bridge were acquired using Leica ScanStation P40, from 9 stations (5 below, 2 on a top and 1 each side) with the sampling step 6.3mm at the measure range of 10.0m. The point clouds from different scanning stations were registered using the artificial targets through Leica Cylone software. The point cloud of the bridge was used to reconstruct a 3D model and identify surface damage. The data set was down-sampled with the sampling step of 5mm.

history
  • 2021-01-28 first online, published, posted
publisher
4TU.ResearchData
format
E57
funding
  • Laser Scanning for Automatic Bridge Assessment (grant code 799149) [more info...] European Commission
organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience & Remote Sensing

DATA

files (2)