Attached: 2 images I wrote a book on spatial networks, using Python, networkx, and osmnx Online version can be found here: https://bgu-geography.com/net/ Comments and ideas are welcome!

What good can you do with an OpenStreetMap road network? OSM has been the basis of several transportation network datasets like SharedStreets, OSMnx, and most recently Overture. Road network owners…

What good can you do with an OpenStreetMap road network? OSM has been the basis of several transportation network datasets like SharedStreets, OSMnx, and most recently Overture. Road network owners…

As part of my thesis, I am using an OSMnx road network acquired with the graph module. From my understanding of Boeing's literature, OSMnx creates a directed network by default. Therefore, for roads that are not tagged as one-way, I would expect the graph to contain two directed edges for each road segment, one in each direction. However, when I examine the exported road network in ArcGIS Pro, I only see a single feature for each road segment. I would have expected to see two. Any experience with this? can the problem lie with ArcGIS Pro and how it define a feature, or is the network really undirected? Any help/thoughts is greatly appreciated. Thank you!

Draw pretty maps from OpenStreetMap data! Built with osmnx +matplotlib + shapely - marceloprates/prettymaps

I need to get all existing OSM types of roads from the area, and I'm searching for a simple way of doing this rather than specifying each type with "|" I've tried to write something like this: place_name = "Moscow" G = ox.graph_from_place(place_name, network_type="all", custom_filter="%s") or just place_name = "Moscow" G = ox.graph_from_place(place_name, network_type="all", custom_filter="highway") However, in the first one I've received an error while the second one did not return all existing OSM values I've scanned OSMnx documentation, but haven't found any shortcuts for all types of roads: https://osmnx.readthedocs.io/en/stable/user-reference.html

I am trying to solve short path analysis via osmnx.distance.k_shortest_paths(G, orig, dest, k, weight='length') I have used this approach as I am limited in the SSL/memory, that is why I am not using osm.get_network or ox.graph_from_place. I want to be able to filter precisely (highways etc...). I have checked G , and I can draw it. Please find attached the code: from pyrosm import OSM, get_data import momepy import matplotlib.pyplot as plt import geopandas as gpd import pandas as pd import osmnx as ox import networkx as nx import scipy as sp from openpyxl import Workbook osm_keys_to_keep = "highway" custom_filter = dict(highway=['trunk', 'motorway', 'motorway_link','primary']) filter_type = "keep" osm = OSM(get_data("palma")) roadtanker = osm.get_data_by_custom_criteria(custom_filter=custom_filter, osm_keys_to_keep=osm_keys_to_keep, filter_type=filter_type) roadtankerline=gpd.GeoDataFrame.explode(roadtanker,ignore_index=True) roadtankerline2=roadtankerline.to_crs(3857) G = momepy.gdf_to_nx(roadtankerline2,approach='dual') print(type(G)) fig, ax = plt.subplots() nx.draw(G, {n:[n[0], n[1]] for n in G.nodes}, ax=ax, node_size=0) target_node = ox.distance.nearest_nodes(G,336678.742,4792756.319) plt.show() I have this message error: Traceback (most recent call last): File "C:\Users\xw6362\PycharmProjects\ES14\Transport 1.py", line 49, in target_node = ox.distance.nearest_nodes(G,336678.742,4792756.319) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\osmnx\distance.py", line 217, in nearest_nodes nodes = utils_graph.graph_to_gdfs(G, edges=False, node_geometry=False)[["x", "y"]] File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\osmnx\utils_graph.py", line 56, in graph_to_gdfs gdf_nodes.index.rename("osmid", inplace=True) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\util\_decorators.py", line 331, in wrapper return func(*args, **kwargs) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\core\indexes\multi.py", line 3821, in set_names return super().set_names(names=names, level=level, inplace=inplace) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\util\_decorators.py", line 331, in wrapper return func(*args, **kwargs) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\core\indexes\base.py", line 1932, in set_names raise TypeError("Must pass list-like as `names`.") TypeError: Must pass list-like as `names`. *I do not know what went wrong as the type of variable seems okay, it may be linked to the indexation but I am not sure. Do you have a path to a solution?

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A 'tidyverse'-friendly toolkit, inspired by the 'OSMnx' 'Python' library, to download, model, simplify, analyze and visualize street networks and other geospatial features from 'OpenStreetMap'. Build routable graphs from a place name, address, point or bounding box; simplify topology; compute shortest paths, isochrones and urban metrics (intersection density, circuity, street-orientation entropy, centrality); and export to 'sf', 'sfnetworks' and 'MapLibre'. Heavy graph computation is performed by a bundled 'Rust' core.

A 'tidyverse'-friendly toolkit, inspired by the 'OSMnx' 'Python' library, to download, model, simplify, analyze and visualize street networks and other geospatial features from 'OpenStreetMap'. Build routable graphs from a place name, address, point or bounding box; simplify topology; compute shortest paths, isochrones and urban metrics (intersection density, circuity, street-orientation entropy, centrality); and export to 'sf', 'sfnetworks' and 'MapLibre'. Heavy graph computation is performed by a bundled 'Rust' core.

Introduction: In the era of smart cities and data-driven urban planning, accessing and analyzing street networks has traditionally been a complex, multi-step process requiring disparate tools and significant manual effort. OSMnx, a powerful Python package developed by Geoff Boeing at the University of Southern California, fundamentally changes this paradigm by enabling users to download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap with just a single line of code.

How software tools can evaluate urban infrastructure and identify opportunities for 15-minute city development. Using Python, OSMnx, and OpenStreetMap data to assess accessibility.

Quelle: GHSL Urban Center Database R2024A (EU JRC, CC BY 4.0), OpenStreetMap über OSMnx (ODbL), World Bank Open Data API (CC BY 4.0).

I need to get all existing OSM types of roads from the area, and I'm searching for a simple way of doing this rather than specifying each type with "|" I've tried to write something like this: place_name = "Moscow" G = ox.graph_from_place(place_name, network_type="all", custom_filter="%s") or just place_name = "Moscow" G = ox.graph_from_place(place_name, network_type="all", custom_filter="highway") However, in the first one I've received an error while the second one did not return all existing OSM values I've scanned OSMnx documentation, but haven't found any shortcuts for all types of roads: https://osmnx.readthedocs.io/en/stable/user-reference.html

I am trying to solve short path analysis via osmnx.distance.k_shortest_paths(G, orig, dest, k, weight='length') I have used this approach as I am limited in the SSL/memory, that is why I am not using osm.get_network or ox.graph_from_place. I want to be able to filter precisely (highways etc...). I have checked G , and I can draw it. Please find attached the code: from pyrosm import OSM, get_data import momepy import matplotlib.pyplot as plt import geopandas as gpd import pandas as pd import osmnx as ox import networkx as nx import scipy as sp from openpyxl import Workbook osm_keys_to_keep = "highway" custom_filter = dict(highway=['trunk', 'motorway', 'motorway_link','primary']) filter_type = "keep" osm = OSM(get_data("palma")) roadtanker = osm.get_data_by_custom_criteria(custom_filter=custom_filter, osm_keys_to_keep=osm_keys_to_keep, filter_type=filter_type) roadtankerline=gpd.GeoDataFrame.explode(roadtanker,ignore_index=True) roadtankerline2=roadtankerline.to_crs(3857) G = momepy.gdf_to_nx(roadtankerline2,approach='dual') print(type(G)) fig, ax = plt.subplots() nx.draw(G, {n:[n[0], n[1]] for n in G.nodes}, ax=ax, node_size=0) target_node = ox.distance.nearest_nodes(G,336678.742,4792756.319) plt.show() I have this message error: Traceback (most recent call last): File "C:\Users\xw6362\PycharmProjects\ES14\Transport 1.py", line 49, in target_node = ox.distance.nearest_nodes(G,336678.742,4792756.319) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\osmnx\distance.py", line 217, in nearest_nodes nodes = utils_graph.graph_to_gdfs(G, edges=False, node_geometry=False)[["x", "y"]] File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\osmnx\utils_graph.py", line 56, in graph_to_gdfs gdf_nodes.index.rename("osmid", inplace=True) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\util\_decorators.py", line 331, in wrapper return func(*args, **kwargs) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\core\indexes\multi.py", line 3821, in set_names return super().set_names(names=names, level=level, inplace=inplace) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\util\_decorators.py", line 331, in wrapper return func(*args, **kwargs) File "C:\Users\xw6362\.conda\envs\ES14\lib\site-packages\pandas\core\indexes\base.py", line 1932, in set_names raise TypeError("Must pass list-like as `names`.") TypeError: Must pass list-like as `names`. *I do not know what went wrong as the type of variable seems okay, it may be linked to the indexation but I am not sure. Do you have a path to a solution?

A few years back we saw a rush of attention to road network software and data from city and county transportation departments, particularly…