gboeing/osmnx
Osmnx
OSMnx is a Python library for downloading, modeling, and analyzing street networks and other geospatial features from OpenStreetMap. It enables users to retrieve and work with real-world infrastructure data anywhere in the world, providing tools for network analysis, spatial queries, and visualization.
The library offers capabilities for working with urban features such as building footprints, transit stops, and elevation data, along with network statistics like intersection density and circuity. It supports multiple travel modes including driving, walking, and biking, and can calculate shortest paths, impute travel speeds, and generate isoline maps. Additional functionality includes geocoding, map-matching, coordinate projection, and the ability to save and load networks in various formats.
OSMnx provides tools for visualizing street networks and geospatial features as static maps or interactive web maps, and can plot figure-ground diagrams. The library is available through standard Python package installation methods.
Features
- Street Network Downloaders - Downloads and models street networks from OpenStreetMap anywhere in the world with a single line of code.
- Location-Based Data Queriers - Queries geospatial data by city name, polygon, bounding box, or point with distance parameters.
- Street Network Visualizations - Provides static and interactive map visualizations of street networks and urban features.
- Urban Feature Analyzers - Analyzes urban features like building footprints, transit stops, and amenities from OpenStreetMap data.
- Travel Mode Modelers - Models driving, walking, biking, and other travel modes as directed graphs for network analysis.
- Geospatial Feature Downloaders - Downloads building footprints, transit stops, and other geospatial features as GeoPandas GeoDataFrames.
- Geospatial Visualizations - Creates static and interactive visualizations of street networks and geospatial features from OpenStreetMap.
- Network Statistics Calculators - Calculates topological and spatial network indicators like intersection density, circuity, and centrality.
- Shortest Path Algorithms - Solves shortest paths on real-world street networks using multiple weight metrics.
- Travel Time Estimation - Calculates travel times and speeds on real-world road networks using imputed data.
- Map Matchers - Matches GPS points, routes, and trajectories to the nearest street network edges or nodes.
- Street Bearing Calculators - Calculates and visualizes street bearings and orientations for urban network analysis.
- Elevation Data Services - Attaches node elevations from raster files or web services and calculates edge grades for street networks.
- Travel Speed Imputers - Imputes missing travel speeds and calculates edge travel times for street network routing.
- Isoline Map Generators - Generates isoline and isochrone maps to visualize travel distance and time from geographic points.
- Network Topology Simplifiers - Simplifies and corrects street network topology by cleaning nodes and consolidating complex intersections.
- Spatial Nearest Element Finders - Finds the nearest node or edge to coordinates using a fast spatial index on street networks.
- Coordinate Projections - Projects graphs to different coordinate reference systems including automatic UTM projection.
- Geocoding Converters - Geocodes place names and addresses to latitude-longitude coordinates using the OpenStreetMap Nominatim API.
- Data Visualization - Download and visualize street networks from OpenStreetMap.
- Geospatial and Vector Mapping - Python library for street network analysis.
- Geospatial Mapping - Python library for modeling and analyzing street networks.
- Programming Libraries - Python visualizer for street networks.
- Python Geospatial Libraries - Downloads and analyzes OpenStreetMap street networks.
Star history
How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
