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Understanding the dynamics of urban areas of interest through volunteered geographic information

Chen, M; Arribas-Bel, D; Singleton, A; (2019) Understanding the dynamics of urban areas of interest through volunteered geographic information. Journal of Geographical Systems , 21 (1) pp. 89-109. 10.1007/s10109-018-0284-3. Green open access

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Abstract

Obtaining insights about the dynamics of urban structure is crucial to the framing of the context within the smart city. This paper focuses on urban areas of interest (UAOI), a concept that provides functional definitions of a city’s spatial structure. Traditional sources of social data can rarely capture these aspects at scale while spatial information on the city alone does not capture how the population values different parts of the city and in different ways. Hence, we leverage volunteered geographic information (VGI) to overcome some of the limits of traditional sources in providing urban structural and functional insights. We use a special type of VGI—metadata from geotagged Flickr images—to identify UAOIs and exploit their temporal and spatial attributes. To do this, we propose a methodological strategy that combines hierarchical density-based spatial clustering for applications with noise and the ‘α-shape’ algorithm to quantify the dynamics of UAOIs in Inner London for a period 2013–2015 and develop an innovative visualisation of UAOI profiles from which UAOI dynamics can be explored. Our results expand and improve upon the previous literature on this topic and provide a useful reference for urban practitioners who might wish to include more timely information when making decisions.

Type: Article
Title: Understanding the dynamics of urban areas of interest through volunteered geographic information
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s10109-018-0284-3
Publisher version: https://doi.org/10.1007/s10109-018-0284-3
Language: English
Additional information: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Social Sciences, Geography, Urban dynamics, Urban areas of interest, Quantitative analysis, Volunteered geographic information, Social media data, TWITTER, PATTERNS
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10128977
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