Geodemographics and residential differentiation: A methodological review and future directions for learned representations of the social landscape

Singleton, Alex and Spielman, Seth E (2026) Geodemographics and residential differentiation: A methodological review and future directions for learned representations of the social landscape COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 125. 102396-. ISSN 0198-9715, 1873-7587

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Abstract

Residential differentiation reflects the complex patterns by which social groups distribute themselves across urban spaces, fundamentally shaping social, economic, and spatial structures. This paper reviews the methodological development of geodemographic classification, tracing its evolution from early social area analysis and factorial ecology through to contemporary approaches. We critically evaluate this lineage of methods for quantifying residential patterns, and identifying persistent limitations in capturing the non-linear complexities of contemporary urban environments. Building on this review, we explore potential future directions involving learned representations of the social landscape, which may offer alternatives to traditional linear dimensionality reduction techniques. Drawing on recent empirical work applying deep learning to geodemographic classification, we consider how such approaches might address identified limitations while acknowledging that their advantages over established methods remain context-dependent and require further empirical validation. We emphasise that any adoption of these techniques must prioritise transparency and interpretability. The paper concludes by outlining potential directions for future research, including how learned representations might be integrated within existing geodemographic workflows.

Item Type:	Article
Uncontrolled Keywords:	Geodemographics, Deep learning, Urban residential structure, Autoencoders, Spatial analysis, Computational geography
Depositing User:	Symplectic Admin
Date Deposited:	20 Jan 2026 15:59
Last Modified:	16 Jun 2026 08:56
DOI:	10.1016/j.compenvurbsys.2025.102396
Open Access URL:	https://doi.org/10.1016/j.compenvurbsys.2025.10239...
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3196712
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