Gray, J orcid.org/0000-0002-7558-1247, Buckner, L orcid.org/0000-0002-5108-5273 and Comber, A orcid.org/0000-0002-3652-7846 (2023) Predicting Gentrification in England: A Data Primitive Approach. Urban Science, 7 (2). 64. ISSN 2413-8851
Abstract
Geodemographic classifications are useful tools for segmenting populations and have many applications but are not suitable for measuring neighbourhood change over time. There is a need for an approach that uses data of a higher spatiotemporal resolution to capture the fundamental dimensions of processes driving local changes. Data primitives are measures that capture the fundamental drivers of neighbourhood processes and therefore offer a suitable route. In this article, three types of gentrification are conceptualised, and four key data primitives are applied to capture them in a case study region in Yorkshire, England. These areas are visually validated according to their temporal properties to confirm the presence of gentrification and are then assigned to a high-level gentrification type. Ensemble modelling is then used to predict the presence, type, and temporal properties of gentrification across the rest of England. The results show an alignment of the spatial extent of gentrification types with previous gentrification studies throughout the country but may have made an overprediction in London. The periodicities of (1) residential, (2) rural, and (3) transport-led gentrification also vary throughout the country, but regardless of type, gentrification in areas within close proximity to one another have differing velocities such that they peak and complete within similar times. These temporal findings offer new, more timely tools for authorities in devising schedules of interventions and for understanding the intricacies of neighbourhood change.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2023 by the authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | data primitives; neighbourhood change; gentrification; urban geography; urban dynamics |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Sociology and Social Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Jul 2023 11:15 |
Last Modified: | 05 Jul 2023 11:15 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/urbansci7020064 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200577 |