Grids#

Generate British National Grid (BNG) grid square data within specified bounds.

Uses a GeoJSON-like mapping for grid squares implementing the __geo_interface__. Use of this protocol enables integration with geospatial data processing libraries and tools.

Grid square data covering the BNG index system bounds is provided as an iterator at 100km, 50km, 10km, 5km and 1km resolutions. GeoPandas can be used to read the iterator data directly into a GeoDataFrame for further processing using geopandas.GeoDataFrame.from_features() or similar methods. Iterators can be converted to lists to generate all grid square GeoJSON-like Features at a given resolution.

osbng.grids.BNG_BOUNDS: tuple[int, int, int, int] = (0, 0, 700000, 1300000)#

BNG index system bounding box.

Expressed as (xmin, ymin, xmax, ymax) using easting and northing coordinates.

Represents the valid extent for BNGReference and grid generation.

Type:

tuple[int, int, int, int]

osbng.grids.bbox_to_bng_iterfeatures(xmin: int | float, ymin: int | float, xmax: int | float, ymax: int | float, resolution: int | str) → Iterator[dict[str, Any]][source]#

Returns an iterator of BNGReference Features given a bounding box and resolution.

Implements the __geo_interface__ protocol. The returned data structure represents the BNGReference object as a GeoJSON-like Feature.

Parameters:

  • xmin (int | float) – The minimum easting coordinate of the bounding box (BBOX).

  • ymin (int | float) – The minimum northing coordinate of the BBOX.

  • xmax (int | float) – The maximum easting coordinate of the BBOX.

  • ymax (int | float) – The maximum northing coordinate of the BBOX.

  • resolution (int | str) – The BNG resolution expressed either as a metre-based integer or as a string label.

Yields:

dict[str, Any] – A GeoJSON-like representation of a BNGReference object.

Raises:

BNGResolutionError – If the resolution is not a valid resolution.

Examples

>>> print(*bbox_to_bng_iterfeatures(530000, 180000, 535000, 185000, "5km"))
{'type': 'Feature', 'properties': {'bng_ref': 'TQ38SW'}, 'geometry':
{'type': 'Polygon', 'coordinates': (((535000.0, 180000.0), (535000.0, 185000.0),
(530000.0, 185000.0), (530000.0, 180000.0), (535000.0, 180000.0)),)}}
>>> print(*bbox_to_bng_iterfeatures(530000, 180000, 535000, 185000, "10km"))
{'type': 'Feature', 'properties': {'bng_ref': 'TQ38'}, 'geometry':
{'type': 'Polygon', 'coordinates': (((540000.0, 180000.0), (540000.0, 190000.0),
(530000.0, 190000.0), (530000.0, 180000.0), (540000.0, 180000.0)),)}}
osbng.grids.bng_grid_100km: Iterator[dict[str, Any]] = <generator object bbox_to_bng_iterfeatures>#

Iterator of GeoJSON-like Features for 100km BNG grid squares within BNG_BOUNDS.

Each yielded dictionary implements the __geo_interface__ for a single 100km BNG grid square and corresponds to a BNGReference at 100 km resolution.

Notes

  • No Features are generated until the iterator is consumed.

  • Convert to a list (list(bng_grid_100km)) to trigger Feature generation.

  • Pass directly to gpd.GeoDataFrame.from_features for GeoDataFrame construction.

osbng.grids.bng_grid_10km: Iterator[dict[str, Any]] = <generator object bbox_to_bng_iterfeatures>#

Iterator of GeoJSON-like Features for 10km BNG grid squares within BNG_BOUNDS.

Each yielded dictionary implements the __geo_interface__ for a single 10km BNG grid square and corresponds to a BNGReference at 10km resolution.

Notes

  • No Features are generated until the iterator is consumed.

  • Convert to a list (list(bng_grid_10km)) to trigger Feature generation.

  • Pass directly to gpd.GeoDataFrame.from_features for GeoDataFrame construction.

osbng.grids.bng_grid_1km: Iterator[dict[str, Any]] = <generator object bbox_to_bng_iterfeatures>#

Iterator of GeoJSON-like Features for all 1km BNG grid squares within BNG_BOUNDS.

Each yielded dictionary implements the __geo_interface__ for a single 1km BNG grid square and corresponds to a BNGReference at 1km resolution .

Notes

  • No Features are generated until the iterator is consumed.

  • Convert to a list (list(bng_grid_1km)) to trigger Feature generation.

  • Pass directly to gpd.GeoDataFrame.from_features for GeoDataFrame construction.

osbng.grids.bng_grid_50km: Iterator[dict[str, Any]] = <generator object bbox_to_bng_iterfeatures>#

Iterator of GeoJSON-like Features for 50km BNG grid squares within BNG_BOUNDS.

Each yielded dictionary implements the __geo_interface__ for a single 50km BNG grid square and corresponds to a BNGReference at 50km resolution.

Notes

  • No Features are generated until the iterator is consumed.

  • Convert to a list (list(bng_grid_50km)) to trigger Feature generation.

  • Pass directly to gpd.GeoDataFrame.from_features for GeoDataFrame construction.

osbng.grids.bng_grid_5km: Iterator[dict[str, Any]] = <generator object bbox_to_bng_iterfeatures>#

Iterator of GeoJSON-like Features for all 5km BNG grid squares within BNG_BOUNDS.

Each yielded dictionary implements the __geo_interface__ for a single 5km BNG grid square and corresponds to a BNGReference at 5km resolution .

Notes

  • No Features are generated until the iterator is consumed.

  • Convert to a list (list(bng_grid_5km)) to trigger Feature generation.

  • Pass directly to gpd.GeoDataFrame.from_features for GeoDataFrame construction.