Evaluating Spatiotemporal Distribution of Residential Sprawl and Influencing Factors Based on Multi-Dimensional Measurement and GeoDetector Modelling

Linlin Zhang, Guanghui Qiao, Huiling Huang, Yang Chen and Jiaojiao Luo
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Linlin Zhang: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Guanghui Qiao: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Huiling Huang: School of Architecture and Civil Engineer, Heilongjiang University of Science and Technology, Harbin 150022, China
Yang Chen: Law School, Ningbo University, Ningbo 315211, China
Jiaojiao Luo: School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, China

IJERPH, 2021, vol. 18, issue 16, 1-18

Abstract: Residential sprawl constitutes a main part of urban sprawl which poses a threat to the inhabitant environment and public health. The purpose of this article is to measure the residential sprawl at a micro-scale using a case study of Hangzhou city. An integrated sprawl index on each 1 km × 1 km residential land cell was calculated based on multi-dimensional indices of morphology, population density, land-use composition, and accessibility, followed by a dynamic assessment of residential sprawl. Furthermore, the method of GeoDetector modeling was applied to investigate the potential effects of location, urbanization, land market, and planning policy on the spatial variation of residential sprawl. The results revealed a positive correlation between CO 2 emissions and residential sprawl in Hangzhou. There has been a remarkable increase of sprawl index on residential land cells across the inner suburb and outer suburb, and more than three-fifths of the residential growth during 2000–2010 were evaluated as dynamic sprawl. The rapid development of the land market and urbanization were noted to impact the spatiotemporal distribution of residential sprawl, as q -statistic values of population growth and land price ranked highest. Most notably, the increasing q -statistic values of urban planning and its significant interactions with other factors highlighted the effects of incremental planning policies. The study derived the policy implication that it is necessary to transform the traditional theory and methods of incremental planning.

Keywords: residential sprawl; multi-dimensional measurement; CO 2 emissions; incremental planning; GeoDetector modeling (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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