Urban spatial structure from a street network perspective: mapping street patterns with random forest classification

Cai Wu*, Jiong Wang, M.J. Kraak

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Street patterns are planar street layouts in a given urban area, which serve as tools for researchers and urban planners to comprehend the structure of urban environments. Nonetheless, the task of mapping street patterns for extensive inter-city studies remains daunting due to the lack of consistency in manual identification methods. With recent technological advancements and data accessibility, new avenues have opened for data-driven techniques in mapping street patterns. This study proposes an innovative framework that employs open data platforms and data processing methods, including network science and supervised machine learning, to map street patterns in cities across the globe effortlessly. Case studies were applied to six cities worldwide and made two key observations from the resulting maps. Firstly, the spatial distribution of street patterns mirrors the urban spatial structure within a city. Secondly, the innate differences between cities become apparent. This study is confident that the novel methodology not only unveils the urban spatial structure across diverse cities but can also be employed to investigate the connection between urban built form and urban activities.
Original languageEnglish
Title of host publicationThe 18th International Conference on Computational Urban Planning and Urban Management
EditorsS. Sangiambut
PublisherCentre for Open Science
Number of pages9
Publication statusPublished - 14 Jul 2023
Event18th International Conference on Computational Urban Planning and Urban Management, CUPUM 2023 - Montreal, Canada
Duration: 20 Jun 202322 Jun 2023
Conference number: 18
https://www.cupum2023.org/

Conference

Conference18th International Conference on Computational Urban Planning and Urban Management, CUPUM 2023
Abbreviated titleCUPUM 2023
Country/TerritoryCanada
CityMontreal
Period20/06/2322/06/23
Internet address

Keywords

  • Street Pattern
  • Urban Spatial Structure
  • Urban Morphology
  • Machine learning

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