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Understanding uneven urban expansion with natural cities using open data

Long, Y; Zhai, W; Shen, Y; Ye, X; (2018) Understanding uneven urban expansion with natural cities using open data. Landscape and Urban Planning , 177 pp. 281-293. 10.1016/j.landurbplan.2017.05.008. Green open access

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Abstract

The last several decades have witnessed a rapid yet uneven urban expansion in developing countries. The existing studies rely heavily on official statistical yearbooks and remote sensing images. However, the former data sources have been criticized due to its non-objectivity and low quality, while the latter is labor and cost consuming in most cases. Recent efforts made by fractal analyses provide alternatives to scrutinize the corresponding “natural urban area”. In our proposed framework, the dynamics of internal urban contexts is reflected in a quasi-real-time manner using emerging new data and the expansion is a fractal concept instead of an absolute one based on the conventional Euclidean method. We then evaluate the magnitude and pattern of natural cities and their expansion in size and space. It turns out that the spatial expansion rate of official cities (OCs) in our study area China has been largely underestimated when compared with the results of natural cities (NCs). The perspective of NCs also provides a novel way to understanding the quality of uneven urban expansion. We detail our analysis for the 23 urban agglomerations in China, especially paying more attention to the three most dominating urban agglomerations of China: Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD). The findings from the OC method are not consistent with the NC method. The distinctions may arise from the definition of a city, and the bottom-up NC method contributes to our comprehensive understanding of uneven urban expansion.

Type: Article
Title: Understanding uneven urban expansion with natural cities using open data
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.landurbplan.2017.05.008
Publisher version: https://doi.org/10.1016/j.landurbplan.2017.05.008
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Urban Expansion; Social Media; Head/Tail Division; New Data; China
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10047107
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