Urban Street Network Analysis in a Computational Notebook

Abstract: 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 buildin

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch
• Anmerkungen: Veröffentlichungsversion ; begutachtet (peer reviewed) ; In: Region: the journal of ERSA ; 6 (2019) 3 ; 39-51

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Mannheim
• (wer): SSOAR - Social Science Open Access Repository
• (wann): 2019
• Urheber: Boeing, Geoff

Weitere Informationen

• DOI: 10.18335/region.v6i3.278
• URN: urn:nbn:de:101:1-2021020515342710461327
• Rechteinformation: Open Access; Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:28 MESZ