Artikel

Urban street network analysis in a computational notebook

Computational notebooks offer researchers, practitioners, students, and educators the ability to interactively run code and disseminate reproducible workflows that weave together code, visuals, and narratives. This article explores the potential of computational notebooks in urban analytics and planning, demonstrating their utility through a case study of OSMnx and its tutorials repository. OSMnx is a Python package for working with OpenStreetMap data and modeling, analyzing, and visualizing street networks anywhere in the world. Its official demos and tutorials are distributed as open-source Jupyter notebooks on GitHub. This article showcases this resource by documenting the repository and demonstrating OSMnx interactively through a synoptic tutorial adapted from the repository. It illustrates how to download and model street networks for various study sites, compute network indicators, visualize street centrality, calculate routes, and work with other spatial data such as building footprints and points of interest. Computational notebooks can empower guides for introducing methods to new users and can help researchers reach broader audiences interested in learning from, adapting, and remixing their work. Due to their utility and versatility, the ongoing adoption of computational notebooks in urban planning, analytics, and related geocomputation disciplines should continue into the future.

Language
Englisch

Bibliographic citation
Journal: REGION ; ISSN: 2409-5370 ; Volume: 6 ; Year: 2019 ; Issue: 3 ; Pages: 39-51 ; Louvain-la-Neuve: European Regional Science Association (ERSA)

Classification
Wirtschaft
Subject
Computational Notebook
Jupyter
OpenStreetMap
OSMnx
Python
Street Network
Urban Planning

Event
Geistige Schöpfung
(who)
Boeing, Geoff
Event
Veröffentlichung
(who)
European Regional Science Association (ERSA)
(where)
Louvain-la-Neuve
(when)
2019

DOI
doi:10.18335/region.v6i3.278
Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Boeing, Geoff
  • European Regional Science Association (ERSA)

Time of origin

  • 2019

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