Li, Qing-Quan;
Yue, Yang;
Gao, Qi-Li;
Zhong, Chen;
Barros, Joana;
(2022)
Towards a new paradigm for segregation measurement in an age of big data.
Urban Informatics
, 1
(1)
, Article 5. 10.1007/s44212-022-00003-3.
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Abstract
Recent theoretical and methodological advances in activity space and big data provide new opportunities to study socio-spatial segregation. This review first provides an overview of the literature in terms of measurements, spatial patterns, underlying causes, and social consequences of spatial segregation. These studies are mainly place-centred and static, ignoring the segregation experience across various activity spaces due to the dynamism of movements. In response to this challenge, we highlight the work in progress toward a new paradigm for segregation studies. Specifically, this review presents how and the extent to which activity space methods can advance segregation research from a people-based perspective. It explains the requirements of mobility-based methods for quantifying the dynamics of segregation due to high movement within the urban context. It then discusses and illustrates a dynamic and multi-dimensional framework to show how big data can enhance understanding segregation by capturing individuals’ spatio-temporal behaviours. The review closes with new directions and challenges for segregation research using big data.
| Type: | Article |
|---|---|
| Title: | Towards a new paradigm for segregation measurement in an age of big data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s44212-022-00003-3 |
| Publisher version: | https://doi.org/10.1007/s44212-022-00003-3 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Inequality, Social segregation, Big data, Activity space, Human mobility |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10155792 |
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