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Published October 15, 2024 | Version v3
Dataset Open

Large-scale 3D building and tree datasets constructed from airborne LiDAR point clouds in Glasgow, UK

Description

This verison provides the tree volume data in raster format.

Urban Big Data Centre of the University of Glasgow generates 3D city models via the airborne LiDAR point clouds acquired between 2020-2021 on behalf of Glasgow City Council. It is a large-scale 3D city model containing 3D information on terrain, trees, and buildings in Glasgow City. This dataset comprises terrain, tree canopy, and building products derived from high-density airborne LiDAR point clouds. 

The terrain products include Digital Terrain Model (DTM), Digital Surface Model (DSM), and normalized Digital Surface Model (nDSM) in 0.5 m spatial resolution. The DTM and DSM rasters were provided by the vendor and nDSM rasters were obtained by subtracting DTM from DSM. Terrain products are provided in 5 km by 5 km GeoTIF format raster.

The tree canopy products are composed of canopy height models (CHM) and tree top locations. Classified tree point clouds were applied with pit-free algorithm to generate CHM in 0.5 m grid raster in GeoTIF format [1]-[2]. Treetop locations were identified by using Local Maximum Filter based on CHM and are recorded as points in Shapefile format. The tree canopy products are provided in 5 km by 5 km tiles.

Building 3D model products include footprint polygons with building height attributes and 3D mesh of building models in LoD1 and LoD2 levels. A series of processes such as converting building point clouds to building height models (BHM), converting BHM to polygons, and polygon regularization were conducted to obtain the building footprint polygons. Building height attributes were calculated from BHM for each footprint. The building footprint data are provided in Shapefile format. LoD1 models were generated based on the footprint and average height of the building. LoD2 models were constructed based on footprint and building point cloud with City3D tool[3]. LoD1 and LoD2 models are provided in OBJ and shapefile format. Building 3D model products are provided in 5 km by 5 km tiles. The RMSE of Euclidean distances between each point in the point cloud to the reconstructed model was calculated to evaluate the LoD2 model construction. A table of RMSE and a note for a few problematic models are provided.

Files

gb_grids_5km_glasgow.zip

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Additional details

Additional titles

Subtitle
Tree volume in grid

Related works

References
Publication: arXiv:2104.04891 (arXiv)
Publication: 10.1109/JURSE57346.2023.10144215 (DOI)

Funding

Economic and Social Research Council
Urban Big Data ES/L011921/1
Economic and Social Research Council
Urban Big Data Centre ES/S007105/1
Glasgow City Council
UBDC GCC 3D City Modelling Project NA

Dates

Collected
2021
LiDAR data were acquired between 2020 - 2021

References

  • [1] Khosravipour, A., Skidmore, A. K., Isenburg, M., Wang, T., & Hussin, Y. A. (2014). Generating pit-free canopy height models from airborne lidar. Photogrammetric Engineering & Remote Sensing, 80(9), 863-872.
  • [2] Roussel, J. R., Auty, D., Coops, N. C., Tompalski, P., Goodbody, T. R., Meador, A. S., ... & Achim, A. (2020). lidR: An R package for analysis of Airborne Laser Scanning (ALS) data. Remote Sensing of Environment, 251, 112061
  • [3] Huang, J., Stoter, J., Peters, R., & Nan, L. (2022). City3D: Large-scale building reconstruction from airborne LiDAR point clouds. Remote Sensing, 14(9), 2254.