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Sustainability 2017, 9(3), 393; doi:10.3390/su9030393

Spatiotemporal Dynamics and Spatial Determinants of Urban Growth in Suzhou, China

1
Department of Geography, University of Utah, Salt Lake City, UT 84112, USA
2
Department of Land Management, Zhejiang University, Hangzhou 310029, China
3
Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY 11973, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Tan Yigitcanlar
Received: 2 January 2017 / Revised: 28 February 2017 / Accepted: 1 March 2017 / Published: 7 March 2017
(This article belongs to the Section Sustainable Urban and Rural Development)
View Full-Text   |   Download PDF [8914 KB, uploaded 8 March 2017]   |  

Abstract

This paper analyzes the spatiotemporal dynamics of urban growth and models its spatial determinants in China through a case study of Suzhou, a rapidly industrializing and globalizing city. We conducted spatial analysis on land use data derived from multi-temporal remote sensing images of Suzhou from 1986 to 2008. Three urban growth types, namely infilling, edge-expansion, and leapfrog, were identified. We used landscape metrics to quantify the temporal trend of urban growth in Suzhou. During these 22 years, Suzhou’s urbanization changed from bottom-up rural urbanization to city-based top-down urban expansion. The underlying mechanism changed from TVE (town village enterprise) driven rural industrialization to FDI (foreign direct investment) driven development zone fever. Furthermore, we employed both global and local logistic regressions to model the probability of urban land conversion against a set of spatial variables. The global logistic regression model found the significance of proximity, neighborhood conditions, and socioeconomic factors. The logistic geographically weighted regression (GWR) model improved the global regression model with better model goodness-of-fit and higher prediction accuracy. More importantly, the local parameter estimates of variables enabled us to exam spatial variations of the influences of variables on urban growth in Suzhou. View Full-Text
Keywords: urban growth; urbanization; landscape metrics; geographically weighted regression (GWR); Suzhou; China urban growth; urbanization; landscape metrics; geographically weighted regression (GWR); Suzhou; China
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhang, L.; Wei, Y.D.; Meng, R. Spatiotemporal Dynamics and Spatial Determinants of Urban Growth in Suzhou, China. Sustainability 2017, 9, 393.

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