Featured graphic. Transport mode choice and the commute to work
Alexander D Singleton (2015). Environment and Planning A: Economy and Space, 47(7), 1401-1403. DOI: 10.1177/0308518X15595752
Abstract
This publication does not contain a traditional abstract. Instead, it presents a featured graphic methodology paper describing the automated production of transport mode choice flow maps using UK 2011 Census travel-to-work data for Kingston upon Hull and all local authority districts in England.
Extended Summary
This research demonstrates an automated approach to visualising commuting patterns and transport mode choices using comprehensive travel-to-work data from the UK 2011 Census of Population. The study utilised origin-destination flow data from middle layer super output areas (MSOAs) in England and Wales, covering geographical units containing between 5,000 and 15,000 people each. The methodology employed the statistical programming language R to automatically generate flow maps as small multiples, showing commuting patterns disaggregated by different transport modes including cycling, walking, driving, motorcycle, and taxi use. For each transport mode combination, the research extracted the top sixty flows and applied Jenks Natural Breaks classification to group flows into five discrete categories, with line widths and colour schemes systematically assigned to represent flow volumes. The automated process also generated LaTeX documents with hyperlinked contents and produced comprehensive Transport Map Books for all local authority districts in England. The case study of Kingston upon Hull reveals distinct spatial patterns in commuting behaviour across different transport modes. Bicycle commuting shows three main employment areas with concentrated flows, whilst walking patterns are more geographically concentrated around the central business and retail district. Motorcycle users display more diffuse commuting patterns, potentially reflecting advantages during heavy traffic conditions or enhanced parking opportunities at destinations. Active travel modes (walking and cycling) demonstrate significant prevalence, though with different spatial characteristics - walking flows are more concentrated whilst cycling flows extend across broader geographical areas. The research contributes to transport geography and urban planning by providing scalable visualisation methods for understanding modal choice patterns in commuting behaviour. These automated mapping techniques enable systematic analysis of travel-to-work patterns across multiple scales and locations, supporting evidence-based transport policy development. The methodology offers practical applications for local authorities seeking to understand commuting flows and plan sustainable transport infrastructure, particularly for promoting active travel modes and reducing carbon emissions from daily commuting journeys.
Key Findings
- Automated flow mapping methodology successfully visualises commuting patterns across different transport modes using UK Census data
- Walking commutes concentrate around central business districts whilst cycling flows extend across broader geographical areas
- Motorcycle users exhibit more diffuse commuting patterns, potentially reflecting traffic efficiency and parking advantages
- Active travel modes show significant prevalence with distinct spatial characteristics across urban employment centres
- Scalable visualisation approach enables systematic transport analysis across all English local authority districts
Citation
@article{singleton2015featured,
author = {Alexander D Singleton},
title = {Featured graphic. Transport mode choice and the commute to work},
journal = {Environment and Planning A: Economy and Space},
year = {2015},
volume = {47(7)},
pages = {1401-1403},
doi = {10.1177/0308518X15595752}
}