OpenStreetMap with OSMnx#
This example shows how to use OSMnx to download and model a street network from OpenStreetMap, visualize centrality, and save the graph as a shapefile, a GeoPackage, or GraphML.
OSMnx is a Python package to retrieve, model, analyze, and visualize OpenStreetMap street networks as NetworkX MultiDiGraph objects. It can also retrieve any other spatial data from OSM as geopandas GeoDataFrames. See https://osmnx.readthedocs.io/ for OSMnx documentation and usage.
import networkx as nx import osmnx as ox ox.config(use_cache=True, log_console=True) # download street network data from OSM and construct a MultiDiGraph model G = ox.graph_from_point((37.79, -122.41), dist=750, network_type="drive") # impute edge (driving) speeds and calculate edge traversal times G = ox.add_edge_speeds(G) G = ox.add_edge_travel_times(G) # you can convert MultiDiGraph to/from geopandas GeoDataFrames gdf_nodes, gdf_edges = ox.graph_to_gdfs(G) G = ox.graph_from_gdfs(gdf_nodes, gdf_edges, graph_attrs=G.graph) # convert MultiDiGraph to DiGraph to use nx.betweenness_centrality function # choose between parallel edges by minimizing travel_time attribute value D = ox.utils_graph.get_digraph(G, weight="travel_time") # calculate node betweenness centrality, weighted by travel time bc = nx.betweenness_centrality(D, weight="travel_time", normalized=True) nx.set_node_attributes(G, values=bc, name="bc") # plot the graph, coloring nodes by betweenness centrality nc = ox.plot.get_node_colors_by_attr(G, "bc", cmap="plasma") fig, ax = ox.plot_graph( G, bgcolor="k", node_color=nc, node_size=50, edge_linewidth=2, edge_color="#333333" ) # save graph to shapefile, geopackage, or graphml ox.save_graph_shapefile(G, filepath="./graph_shapefile/") ox.save_graph_geopackage(G, filepath="./graph.gpkg") ox.save_graphml(G, filepath="./graph.graphml")
Total running time of the script: ( 0 minutes 5.996 seconds)