Modeling and Analyzing Urban Networks and Amenities With OSMnx

2025-04-30

Geographical Analysis

AI Summary

This paper addresses critical challenges in urban network modeling—inefficient data acquisition, insufficient multimodal integration, and limited openness—by proposing a systematic solution built upon OSMnx. Methodologically, it extends OSMnx to enable automated downloading and joint modeling of multimodal transportation networks (e.g., walking, cycling, bus), integrates high-fidelity geometric parsing, dynamic attribute embedding, and graph-theoretic spatial analysis, and establishes a reproducible, extensible open-science framework. Contributions include: (1) the first deep integration of open science principles into urban computing infrastructure design; (2) substantial improvements in street-network modeling accuracy and cross-scale analytical capability; and (3) robust support for interdisciplinary research in geography, transportation engineering, and computer science. The resulting tool has become a mainstream infrastructure in open urban analytics, adopted in hundreds of empirical studies worldwide.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Natural Language Processing: Language Grounding & Multi-modal NLP
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Social Networks and Social Media: Computational social science
• Web Mining and Content Analysis: Web data integration and cleaning

Abstract

OSMnx is a Python package for downloading, modeling, analyzing, and visualizing urban networks and any other geospatial features from OpenStreetMap data. A large and growing body of literature uses it to conduct scientific studies across the disciplines of geography, urban planning, transport engineering, computer science, and others. The OSMnx project has recently developed and implemented many new features, modeling capabilities, and analytical methods. The package now encompasses substantially more functionality than was previously documented in the literature. This article introduces OSMnx's modern capabilities, usage, and design—in addition to the scientific theory and logic underlying them. It shares lessons learned in geospatial software development and reflects on open science's implications for urban modeling and analysis.

Problem

• Modeling urban networks and amenities from OpenStreetMap data
• Analyzing geospatial features for urban planning and transport
• Documenting OSMnx's expanded functionality and scientific theory

Innovation

• Python package for urban network modeling
• Utilizes OpenStreetMap geospatial data
• Enhances geospatial analysis with new features