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Identification of Spatial Economic Development Model in Chengyu Urban Agglomeration County by Applying Exploratory Spatial Data Analysis

In: Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Zhenchuan Yang

    (Chongqing University)

Abstract

Using the average Night-Time Light Data in the Chengyu Urban Agglomeration County from 2012 to 2019, the spatial weight matrix is defined based on the rook and arc distance contiguity, and the global and local spatial autocorrelation methods in the Exploratory Spatial Data Analysis are used to assess the spatial economic development model of the Chengyu Urban Agglomeration County. The results show that based on rook contiguity, the spatial autocorrelation intensity of the economic development of the Chengyu Urban Agglomeration County can be divided into four ups and downs: in the two phases of 2012–2014 and 2015–2017, the intensity of spatial autocorrelation was on the rise, and the polarization of economic layout was eased; in the two phases of 2014–2015 and 2017–2019, the intensity of spatial autocorrelation was on the decline, the polarization of the economic layout has intensified. Based on the arc distance contiguity, it is preliminarily inferred that the economic impact area of the counties of the Chengyu Urban Agglomeration is about 150 km. Under the two contiguity rules, the economy of the Chengyu Urban Agglomeration County shows a “dual-core” agglomeration development model centered on the downtown area of Chengdu and the main urban area of Chongqing. However, the economic development of other regions needs to be further explored and driven.

Suggested Citation

  • Zhenchuan Yang, 2021. "Identification of Spatial Economic Development Model in Chengyu Urban Agglomeration County by Applying Exploratory Spatial Data Analysis," Springer Books, in: Xinhai Lu & Zuo Zhang & Weisheng Lu & Yi Peng (ed.), Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate, pages 1059-1071, Springer.
  • Handle: RePEc:spr:sprchp:978-981-16-3587-8_70
    DOI: 10.1007/978-981-16-3587-8_70
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