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Sustainability 2018, 10(8), 2800; https://doi.org/10.3390/su10082800

A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns

1
Department of Surveying and Geo-Informatics, Central South University, Changsha 410084, China
2
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
3
College of Resources and Environment Sciences, Hunan Normal University, Changsha 410081, China
4
Key Laboratory of Geospatial Big Data Mining and Application, Hunan Province, Changsha 410081, China
*
Authors to whom correspondence should be addressed.
Received: 26 June 2018 / Revised: 31 July 2018 / Accepted: 4 August 2018 / Published: 7 August 2018
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Abstract

Understanding regional economic agglomeration patterns is critical for sustainable economic development, urban planning and proper utilization of regional resources. Taking Guangdong Province of China as the study area, this paper introduces a comprehensive research framework for analyzing regional economic agglomeration patterns and understanding their spatiotemporal characteristics. First, convergence and autocorrelation methods are applied to understand the economic spatial patterns. Then, the intercity spatial interaction model (ISIM) is proposed to measure the strength of interplay among cities, and social network analysis (SNA) based on the ISIM is utilized, which is designed to reveal the network characteristics of economic agglomerations. Finally, we perform a spatial panel data analysis to comprehensively interpret the influences of regional economic agglomerations. The results indicate that from 2001 to 2016, the economy in Guangdong showed a double-core/peripheral pattern of convergence, with strengthened intercity interactions. The strength and external spillover effects of Guangzhou and Shenzhen enhanced, while Foshan and Dongguan had relatively strong absorptive abilities. Moreover, expanding regional communication and cooperation is key to enhancing vigorous economic agglomerations and regional network ties in Guangdong by spatial panel data analysis. Our results show that this is a suitable method of reflecting regional economic agglomeration process and its spatiotemporal pattern. View Full-Text
Keywords: Guangdong Province; economic agglomeration; network interaction structure; social network analysis; intercity spatial interaction model Guangdong Province; economic agglomeration; network interaction structure; social network analysis; intercity spatial interaction model
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Jin, R.; Gong, J.; Deng, M.; Wan, Y.; Yang, X. A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns. Sustainability 2018, 10, 2800.

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