Inequalities in experiencing urban functions. An exploration of human digital (geo-)footprints
Bibliographic Data
| ID | 21247454 |
|---|---|
| Authors | Alessia Calafiore (0000-0002-5953-2891, University of Edinburgh, corresponding author), Krasen Samardzhiev (University of Liverpool), Francisco Rowe (0000-0003-4137-0246, University of Liverpool), Martin Fleischmann (0000-0003-3319-3366, Charles University), Daniel Arribas-Bel (0000-0002-6274-1619, University of Liverpool) |
| Year | 2024 |
| Volume | 51 |
| Issue | 7 |
| Pages | 1463-1477 |
| Publication date | 2024-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning B Urban Analytics and City Science (JOURNAL) |
| Journal identifiers | ISSN: 2399-8083 • E-ISSN: 2399-8091 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/23998083231208507 |
| OpenAlex | W4388455128 |
| Language | EN |
| Citations received | 3 |
| References cited | 24 |
Studies on mobility inequalities have so far mostly relied on Survey data or Censuses. While such studies have demonstrated that inequalities strongly influence everyday mobility choices, these data sources lack granular information on people’s movements on a daily basis. By capitalising on high spatio-temporal resolution data provided by Spectus.ai, this study aims at investigating how the deprivation level of the area where people live influences the kinds of urban environment they are more likely to use for their everyday activities. To do this, raw GPS trajectories collected in 2019 in Great Britain (GB) are transformed into semantic trajectories where short-time changes and the functional nature of urban contexts are acknowledged as two key dimensions to understand human spatial behaviours. Hourly sequences of stops are extracted from GPS trajectories and enriched with contextual information based on a new area-based classification detecting urban functions. The data exploration shows that some human patterns are widely common across all levels of deprivation, such as the tendency to be mostly exposed to the urban context near the home location. At the same time, we show that differences exist, especially between those who live in the most deprived areas and those who live in the least deprived areas of GB. It appears that people living in the most deprived areas tend to have a less regular working pattern and be more exposed to urban-based functions and well-served areas, while those living in the least deprived areas have a more regular working patterns and are mostly exposed to the countryside and low-density areas. Our approach and results provide new insights on the temporal and contextual dimensions of mobility inequalities, informing on who is exposed to issues characterising certain urban environments
Cartography · Geography · Inequality · Human Mobility and Location-Based Analysis · Impact of Light on Environment and Health · Mathematics · Urban Transport and Accessibility
Understanding individual human mobility patterns
On the influence of density and morphology on the Urban Heat Island intensity
Relationships between Land Use, Socioeconomic Factors, and Travel Patterns in Britain
Gender gaps in urban mobility
Topoi – A method for analysing settlement units and their linkages in an urban–rural fabric
Understanding commuting patterns and changes
Gender inequality in mobility and mode choice in Pakistan
Urban exodus? Understanding human mobility in Britain during the Covid‐19 pandemic using Meta‐Facebook data
The rural–urban interface
The suburbanisation of poverty in British cities, 2004-16
Spatial Signatures - Understanding (urban) spaces through form and function
Beyond Space (As We Knew It)
Disability and Discourses of Mobility and Movement
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |