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Quickstart

This guide walks you through generating your first feature-rich urban network in a few lines of code.

1. Import and create a map

import urbanity

# Create an interactive map centred on a country
m = urbanity.Map(country="Singapore")
m

This opens an interactive ipyleaflet map. You can:

  • Draw a polygon — use the polygon tool in the toolbar to trace your area of interest
  • Draw a bounding box — use the rectangle tool for a quick rectangular selection 
    m.add_bbox()
  • Load a shapefile — pass an existing GeoDataFrame directly (see below) Shapefile 
    m.add_polygon_boundary('path_to_shapefile')

Working in Jupyter

The interactive map works in JupyterLab and Jupyter Notebook. For scripts, pass a shapefile directly instead.

To use an existing polygon assign it directly to the polygon_bounds properties attribute:

import geopandas as gpd

boundary = gpd.read_file('path_to_shapefile')
G.polygon_bounds = boundary

2. Obtain street network

After drawing your area on the map:

# Build a driving network for the drawn area
m.get_network_layer(add_svi=False)
intersections, streets = m.network[1], m.network[2]

Supported network_type values: "drive", "walk", "bike", "all".

Visualise street network

fig, ax = plt.subplots(figsize=(10, 10))

streets.plot(ax=ax, color="black", linewidth=0.5)
intersections.plot(ax=ax, color="orange", markersize=2, zorder=2)

plt.show()

Next Steps