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A circuity temporal analysis of urban street networks using open data: a Lisbon case study

Abstract

Urban street networks impact urban space usage and movement across a city. Circuity, the ratio of network distances to straight-line distances, is considered a critical measurement in urban network morphology and transportation efficiency as it can measure the attractiveness of routes in terms of distance traveled. Here, we compare circuity measures for drivable, cyclable, and walkable networks to analyze how they evolved and understand whether urban changes have produced meaningful circuity changes. Our analyses rely on Lisbon data from OpenStreetMaps to explore circuity for the period 2013-2020, which we used to simulate 4.8 million routes using OpenRouteService to compute the different modes' circuity measures. Our findings suggest that it is crucial to analyze each transport network type separately when planning or modeling urban street networks. Their composition and design differ significantly from mode to mode, such as their attractiveness to users. We identify significant changes in modes' circuity over time, especially in cycling, following Lisbon's cycling infrastructure expansion. Our paper demonstrates that the circuity indicator is useful when planning and modeling street networks, in particular, to optimize the location choice for interventions required to increase the attractiveness of active modes and promote sustainable mobility. At the same time, we emphasize the lack of information on walking infrastructures required for more detailed analyses.

Usage

  1. Main (circuity) analysis (01-circuity_analysis.ipynb)
  2. Inequalities analysis (02-inequalities-gini.ipynb)
  3. Waytypes analysis (03-routes-waytypes.ipynb)
  4. Lisbon's cycleways (04-lisbon-cicleways.ipynb)
  5. Lisbon's road network length (05-osm_data_road_length.ipynb)

If you wish to generate points and compute routes:

  1. Dowload OSM data for the Lisbon area
  2. Setup a OpenRouteService server
  3. Setup the Random Sampling (RS) points and compute their routes (RS_points_routes.py)
  4. Setup the Mobility Survey Sampling (MSS) based points and compute their routes (MSS_points.py & MSS_routes.py)

License

Our code is under MIT license.

Citation

If you find this project useful for your research, please use the following BibTeX entry.

@article{costa2021circuity,
    AUTHOR = {Costa, Miguel and Marques, Manuel and Moura, Filipe},
    TITLE = {A Circuity Temporal Analysis of Urban Street Networks Using Open Data: A Lisbon Case Study},
    JOURNAL = {ISPRS International Journal of Geo-Information},
    VOLUME = {10},
    YEAR = {2021},
    NUMBER = {7},
    ARTICLE-NUMBER = {453},
    URL = {https://www.mdpi.com/2220-9964/10/7/453},
    ISSN = {2220-9964},
    DOI = {10.3390/ijgi10070453}
}