PointER
A LiDAR-Derived Point Cloud Dataset of One Million English Buildings Linked to Energy Characteristics
Science Score: 33.0%
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○CITATION.cff file
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○codemeta.json file
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✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: nature.com -
✓Committers with academic emails
2 of 5 committers (40.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (15.1%) to scientific vocabulary
Keywords
Repository
A LiDAR-Derived Point Cloud Dataset of One Million English Buildings Linked to Energy Characteristics
Basic Info
- Host: GitHub
- Owner: kdmayer
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://www.nature.com/articles/s41597-023-02544-x
- Size: 11.9 MB
Statistics
- Stars: 13
- Watchers: 2
- Forks: 2
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
Points for Energy Renovation (PointER):
A LiDAR-Derived Point Cloud Dataset of One Million English Buildings Linked to Energy Characteristics
Getting Started
- Please see our setup documentation for a step by step description.
- Please check our related open access paper for information about the method and the resulting dataset.
- A dataset comprising one million building point clouds with half of the buildings linked to energy features is available here.
Prerequisites
- Required packages are documented in the environment.yml file.
- The environmentforanalysis.yml includes some more packages required for visualization and analysis.
Running the Code
- To run an example point cloud generation, please use the jupyter notebook.
- To run the point cloud generation for an entire area of interest, please see the point cloud generation documentation.
- The main program can be found here. Please note, that the point cloud generation process involves some upfront data preparation.
The process involves 6 steps:

Due to the size of the point cloud files, it is recommended to set up the container on a machine with a large working memory. We ran the code without problems on a machine with 48 GB, but a machine with 16 GB or more should work.
Dataset
The dataset contains one million building point clouds for 16 Local Authority Districts in England. These Local Authority Districts are representative for the English building stock and selected across the country (see image).

This is an example of a resulting point cloud:

Data Sources
- Point cloud data (.laz): UK National LiDAR Programme
- Open Government Licencse
- We use Verisk UKBuildings database (.gpkg format) as building footprints
- License for personal use only
- Alternatively, we can use OSM data
- Local Authority Distric Boundaries (.shp format)
- Open Government Licencse
- Unique Property Reference Numbers (UPRN) including coordinates (.gpkg format)
- Open Government Licencse
Versioning
V0.1 Initial version
Citation
@article{Krapf2023,
doi = {10.1038/s41597-023-02544-x},
url = {https://doi.org/10.1038/s41597-023-02544-x},
year = {2023},
publisher = {Springer Science and Business Media {LLC}},
volume = {10},
author = {Sebastian Krapf and Kevin Mayer and Martin Fischer},
title = {Points for energy renovation ({PointER}): A point cloud dataset of a million buildings linked to energy features},
journal = {Scientific Data}
}
License
This project is licensed under the MIT License.
Owner
- Name: Kevin
- Login: kdmayer
- Kind: user
- Location: Stanford
- Company: Stanford University
- Website: https://kdmayer.github.io/
- Repositories: 26
- Profile: https://github.com/kdmayer
PhD Candidate at Stanford.
GitHub Events
Total
- Watch event: 1
- Fork event: 1
Last Year
- Watch event: 1
- Fork event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| ADS\ga73pag | s****f@t****e | 114 |
| Kevin | k****2@g****m | 72 |
| ADS\ga73pag | k****f@f****e | 33 |
| vagrant | v****t@v****m | 4 |
| SebastianKrapf | 6****f | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 2
- Total pull requests: 4
- Average time to close issues: 7 days
- Average time to close pull requests: 19 days
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 2.5
- Average comments per pull request: 0.75
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- kdmayer (2)
Pull Request Authors
- SebastianKrapf (3)
- kdmayer (1)