cityImage.classify_land_uses_intoDMAs#

cityImage.classify_land_uses_intoDMAs(buildings_gdf, land_uses_column='land_uses', macro_to_dma=None)[source]#

Classify cityImage land-use groups into DMA functional categories.

The DMA categories are live, work, visit, and mixed combinations of those functions. Input labels should already be normalised cityImage land-use groups, for example values derived from OSM shop, amenity, office, tourism, leisure, or building tags.

Parameters:

  • buildings_gdf (geopandas.GeoDataFrame) – Building table containing normalised land-use labels.

  • land_uses_column (str) – Column containing list-like land-use groups.

  • macro_to_dma (dict[str, str] | None) – Mapping from macro groups to DMA categories.

Returns:

Copy of the building table with DMA classifications.

Return type:

geopandas.GeoDataFrame