urbanflow.utils.sommarioni_utils

sommarioni_utils.py

Util functions to process 1808 Sommarioni Cadaster

Functions

load_sommarioni_layers(path[, target_crs])

Load and split the 1808 Sommarioni cadaster dataset into thematic layers.
urbanflow.utils.sommarioni_utils.load_sommarioni_layers(path, target_crs='EPSG:32633')

Load and split the 1808 Sommarioni cadaster dataset into thematic layers.

Reads a GeoJSON or Feather file of cadaster geometries, filters them by geometry_type, and returns four separate GeoDataFrames: buildings, streets, canals, and courtyards. All layers are re-projected to the target CRS.

Parameters:

  • path (str) – Path to the cadaster file. May be GeoJSON (default) or Feather.

  • target_crs (str or int, optional) – Coordinate reference system to reproject the data into. Defaults to "EPSG:32633" (UTM zone 33N, meters).

Returns:

  • buildings (geopandas.GeoDataFrame) – Polygons labeled as "building" in the input data.

  • streets (geopandas.GeoDataFrame) – Polygons labeled as "street" or "sottoportico".

  • canals (geopandas.GeoDataFrame) – Polygons labeled as "water".

  • courtyards (geopandas.GeoDataFrame) – Polygons labeled as "courtyard".

Return type:

tuple[GeoDataFrame, GeoDataFrame, GeoDataFrame, GeoDataFrame]

Notes

  • If input file is Feather, geopandas.read_feather is used. Otherwise geopandas.read_file is used.

  • Buildings that are stored as MultiPolygons are exploded into single polygons for cleaner rasterization.

  • The function prints the path if it is not a Feather file (for debugging).

Examples

>>> from urbanflow.utils.sommarioni_utils import load_sommarioni_layers
>>> buildings, streets, canals, courtyards = load_sommarioni_layers("sommarioni.geojson")
>>> buildings.crs
<Derived CRS: EPSG:32633>
Name: WGS 84 / UTM zone 33N
Axis Info [cartesian]:
- E[east]: Easting (metre)
- N[north]: Northing (metre)