Modelling active travel accessibility at the micro-scale using multi-source built environment data

Bibliographic Data

ID7150564
AuthorsCorin Staves (University of Cambridge, corresponding author), Irena Itova (0000-0002-3559-1424, University of Cambridge), Belen Zapata-Diomedi (0000-0002-9238-0375, University of Cambridge), Audrey de Nazelle (0000-0002-1092-3971, Imperial College London), Jenna Panter (0000-0001-8870-718X, University of Cambridge), Lucy Gunn (0000-0002-9309-3626), Alan Both (0000-0003-4021-9632), Yuchen Li (0000-0003-1670-3782, University of Cambridge), Ismaïl Saadi (0000-0002-3569-1003, University of Cambridge), James Woodcock (0000-0003-4769-5375, University of Cambridge), M Labib, S M Labib (0000-0002-4127-2075, Utrecht University)
Year2025
Volume119
Pages102270
Publication date2025-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueComputers Environment and Urban Systems (JOURNAL)
Journal identifiersISSN: 0198-9715 • E-ISSN: 1873-7587
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.compenvurbsys.2025.102270
OpenAlexW4408224484
LanguageEN
Citations received2
References cited73

Accessibility models explore how land use and transport systems interact to facilitate access to activities and daily needs. Existing applications generally model accessibility based on distance or travel time. For pedestrians and cyclists, the street-level environment (e.g., green visibility, streetside amenities, dedicated infrastructure) significantly influences people's willingness and ability to travel. Incorporating these features into accessibility models can help them to be more representative of active travellers' experienced environment. This study presents a methodology for incorporating the street-level environment into active mode accessibility. First, micro-scale built environment data from multiple sources are harmonised into a high-resolution digital representation of the land use and transport system. Second, a compute-optimised framework is developed for modelling accessibility at the micro-scale (i.e., each dwelling separately) incorporating the street-level environment. The methods build upon the open geodatabase OpenStreetMap and open-source MATSim project, facilitating expandability and transferability to other contexts. We apply this methodology to develop policy-relevant accessibility indicators for Greater Manchester. In the results, we observe that the street-level environment can cause accessibility indicators to vary at the micro-scale, especially in less connected neighbourhoods where the choice of routes is limited. We also observed that for cyclists, the accessibility advantage over walking reduces substantially when traffic stress is considered. Our findings support further adoption of micro-scale built environment data and high-resolution analysis methods for active travel accessibility modelling in research and practice

Cartography · Geography · Transport engineering · Computer Science · Engineering · Noise Effects and Management · Smart Parking Systems Research · Urban Transport and Accessibility

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