Identification of “Growth” and “Shrinkage” Pattern and Planning Strategies for Shrinking Cities Based on a Spatial Perspective of the Pearl River Delta Region
Publication: Journal of Urban Planning and Development
Volume 146, Issue 4
Abstract
There are two opposing trends in urban development: one is the exponential growth of cities and the other is shrinking cities,” which are characterized by a decrease in number of residents. Since the 2008 financial crisis, there have been great changes in the Pearl River Delta (PRD), where growing and shrinking areas coexist. In this paper, we analyze cities' growth and shrinkage in respect of urban construction and economic vitality in the PRD in spatial term. Thus, we define land use changes in urban construction to characterize growth by using Landsat Thematic Mapper data on urban built-up areas of the PRD region in 2000, 2009, and 2013; and we characterize economic activities for vitality by using Defense Meteorological Satellite Program/Operational Linescan System nighttime light data in various years after time continuous correction and vegetation correction, in combination with population data. Four different types of space are identified in this region, namely continuous growth, transformational growth, stationary, and shrinkage. This paper provides policy recommendations and planning strategies for the future development of shrinking cities in China. Shrinkage is considered to be only a short-term stage in the urbanization process faced by most cities in China and abroad. Technological progress and industrial transformation are likely to be critical factors affecting the direction of urban development, where cities can resume growth from shrinkage by revitalizing manufacturing industry and economic activities through education, innovation, and technology.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. (Nighttime light data, https://www.ngdc.noaa.gov/eog/dmsp/downloadV4composites.html; LandScan population data, https://landscan.ornl.gov/landscan-datasets). Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
This research was funded by a grant from National Natural Science Foundation of China (No. 41571118, 41801163), Natural Science Foundation of Guangdong Province (2018A030313221), Soft Science Research Program of Science and Technology Planning Project of Guangdong Province (2018A070712019), and Fundamental Research Funds for Central Universities of the Central South University (18lgpy12). The authors would like to thank Prof. Gang-Len Chang for his comments and support. The authors are also grateful for the data archived from NOAA and ORNL. The authors declared no conflicts of interest with respect to the research, authorship, and/or publication of this article.
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Received: Oct 20, 2019
Accepted: May 19, 2020
Published online: Aug 10, 2020
Published in print: Dec 1, 2020
Discussion open until: Jan 10, 2021
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