Introduction to OSMnx

OSMnx is a Python package that allows users to easily download, construct, and visualize street networks from OpenStreetMap. The package is particularly useful for researchers and analysts who work with geographic data, as it allows them to quickly and easily obtain the information they need to conduct their analyses.

What are the features of OSMnx?

One of the key features of OSMnx is its ability to download street network data from OpenStreetMap. This data is available for any location in the world and can be downloaded in a variety of formats. Once the data has been downloaded, it allows users to easily construct the network, meaning that they can quickly and easily create maps of the street networks for their chosen area.

In addition to its ability to download and construct street networks, OSMnx also provides a number of tools for visualizing and analyzing these networks. For example, users can calculate the shortest path between two points on the network, measure the accessibility of a particular location, or calculate network metrics such as centrality and connectivity. 

Osmnx allows the users to download other spatial geometries such as place boundaries, building footprints, or points of interest as a GeoDataFrame.

You can specify the location to download from using a city name, polygon, bounding box, or point/address and network distance. 

The package also allows users to choose the type of network to download, such as drivable, walkable, bikeable, or all street networks. 

Osmnx has fast map-matching capabilities for points, routes, or trajectories to nearest graph edges or nodes. The package allows users to save networks to disk in various formats, such as shapefiles, GeoPackages, and GraphML.

These tools make it easy for users to gain insight into the structure of a street network and can be used to answer a wide range of questions about the geography of a given area.

Another key advantage of OSMnx is that it is open source. This means that anyone can use the package for free and that the source code is available for anyone to view and modify. This makes it an excellent resource for those looking to work with street network data, as it provides a powerful and flexible platform for performing a wide range of analyses.

How to use ?

To install with Conda:

conda config –prepend channels conda-forge
conda create -n ox –strict-channel-priority osmnx

Or you can install it without Conda by getting the latest requirements.txt file from the OSMnx GitHub repo

Then install all the requirements with: 

python3 -m pip install -r requirements.txt

Then install with pip command: 

python3 -m pip install osnmx

Once it is installed, you can use it to download and model street networks from OpenStreetMap. For example, to download and model the street network for the city of Ohio, you could use the following code:

import osmnx as ox
place_name = “Ohio, USA”
graph = ox.graph_from_place(place_name)

This code will download the street network for Ohio from OpenStreetMap, and construct a networkx graph object representing the network. You can then use this graph object to analyze and visualize the street network, using the built-in functions and methods provided by osmnx and networkx. 

Overall, it is a valuable tool for anyone who needs to work with street network data. Whether you are a researcher, analyst, or simply someone who is curious about the structure of street networks, it is an excellent resource to have in your toolkit.

Click here for implementation in python

Reference Links:


Click here for more blogs

Follow on LinkedIN

Leave a comment

Verified by ExactMetrics