Clarifying bicycling accessibility
Bibliographic Data
| ID | 12293103 |
|---|---|
| Authors | Scott N Lieske (0000-0001-6335-6117, The University of Queensland, corresponding author), Lihong Zhang (0009-0003-0439-8124, The University of Queensland), Simone Leão (0000-0002-2455-5508, The University of Queensland), Simone Z Leao, Dorina Pojani (0000-0002-2018-6338, The University of Queensland), Richard J Buning (0000-0002-0089-3967, The University of Queensland) |
| Year | 2025 |
| Volume | 129 |
| Pages | 104450-104450 |
| Publication date | 2025-10-21 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Transport Geography (JOURNAL) |
| Journal identifiers | ISSN: 0966-6923 • E-ISSN: 1873-1236 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jtrangeo.2025.104450 |
| OpenAlex | W4415378835 |
| Language | EN |
| References cited | 29 |
There is considerable inconsistency in conceptual and empirical approaches to cycling accessibility assessment. As a consequence, prior research results are largely incomparable. This causes confusion and dilutes the impact of cycling research at a time when a shift toward active transport is paramount. At this stage, researchers and practitioners need conceptual and empirical clarity, as well as methodological convergence and standardization. This article synthesizes ideas and approaches to bicycling accessibility assessments and translates these ideas into a conceptually and empirically clear and validated model. We test and refine an existing cycling accessibility index in three cities in six focal areas: 1) alternative destination categories, 2) cleaning and clustering points of interest, 3) network vs. Euclidean distances, 4) alternative areal analysis units, 5) comparison of modified with original model outputs, 6) sub-model influence assessment, and also validate the index with bicycling ridership data. The resulting index incorporating refined destination categories, cleaned POI data, and Euclidean distances calculated for census statistical areas is transferable and contributes to conceptual and empirical clarity in bicycling accessibility assessment. • We survey, test and extend prior research in bicycling accessibility assessment. • A refined index is based on tests of six focal areas. • Bicycling accessibility can be simplified to a valid activity-based approach. • Separating infrastructure from accessibility modelling improves conceptual clarity. • Infrastructure can be included in a broader bikeability assessment
CLARITY · Conceptual framework · Conceptual model · Confusion · Cycling · Empirical research · Index (typography · Jaccard index · Smart Parking Systems Research · Transportation and Mobility Innovations · Urban Transport and Accessibility
Assessing bikeability with street view imagery and computer vision
Comparing alternative approaches to measuring the geographical accessibility of urban health services
A city of cities
Introducing the “15-Minute City”
Developing urban biking typologies
Cycling down under
Measuring non-motorized accessibility
Understanding the effect of sociodemographic, natural and built environment factors on cycling accessibility
Spatio-temporal patterns of a Public Bicycle Sharing Program
Accessible accessibility research challenges
Accessibility evaluation of land-use and transport strategies
Bikeability – Urban structures supporting cycling. Effects of local, urban and regional scale urban form factors on cycling from home and workplace locations in Denmark
| Citation velocity | historical |
|---|---|
| Highly cited | No |