Grid datasets providing boundaries and identifiers for the Ordnance Survey (OS) British National Grid (BNG) index system at multiple spatial resolutions.
These datasets include grid square boundaries and associated identifiers as BNG references covering the bounds (0, 0, 700000, 1300000)
of the BNG index system. Data is supplied in both GeoParquet and GeoPackage (GPKG) formats. The GPKG is provided using 7-Zip compression .7z
due to the GitHub file size limits.
The repository also contains the Python script used for data generation and a Jupyter notebook demonstrating custom grid creation with the osbng
Python package.
Grid data is provided for the following 'standard' and 'intermediate' (quadtree) BNG resolutions:
- 100km
- 50km
- 10km
- 5km
- 1km
Grid data at additional BNG resolutions or for custom geographic extents can be generated by applying the same methods with different parameters. See the notebook create_osbng_grids_examples.ipynb
for examples of creating custom BNG grid datasets.
Ensure system dependencies like GEOS/PROJ/GDAL are installed, then install from the requirements.txt
file:
pip install -r requirements.txt
Create a conda
environment using the environment.yml
file:
conda env create -f environment.yml
conda activate osbng-grids
The OS BNG index system (also known as the OS National Grid) is a rectangular Cartesian 700 x 1300km grid system based upon the transverse Mercator projection. In the BNG, locations are specified using coordinates, eastings (x) and northings (y), measured in meters from a defined origin point (0, 0) southwest of the Isles of Scilly off the coast of Cornwall, England. Values increase to the northeast, covering all of mainland GB and surrounding islands.
The BNG index system is structured using a hierarchical system of grid squares at various resolutions. The BNG uses BNG references, also known more simply as grid or tile references, as grid square identifiers. At its highest level, the grid divides GB into 100 km by 100 km squares, each identified by a two-letter code. Successive levels of resolution further subdivide the grid squares into finer detail, down to individual 1-meter squares.
Please acknowledge Ordnance Survey when using the grid datasets.
The code in this repository is licensed under the the MIT License.
The grid datasets (in the osbng-grids/data
directory) are licensed under the the Open Government Licence v3.0.