GEOGRAPHICAL RESEARCH ›› 2014, Vol. 33 ›› Issue (9): 1736-1746.doi: 10.11821/dlyj201409014

• Orginal Article • Previous Articles     Next Articles

A research on Shenzhen’s industrial spatial structure based on PCA-SOM

Wen ZHANG1,2(), Jiaqiu WANG3   

  1. 1. Geography and Planning School of Sun Yat-sen University, Guangzhou 510275, China
    2. Key Laboratory of Urbanization and Geographical Environment Simulation of Guangdong Province, Guangzhou 510275, China
    3. Centre for Advanced Spatial Analysis of University College London, London W1T 4TJ, Britain
  • Received:2013-06-11 Revised:2013-10-23 Online:2014-09-20 Published:2014-11-10


By using spatial distribution data of Shenzhen enterprises, regarding subdistricts as the basic spatial unit, this paper adopts the principal component analysis (PCA) method to extract factors to achieve the objective of dimension reduction and properties abstraction on industry variables. Based on the above, self-organizing map (SOM) neural network clustering model is built with three industrial characters of the subdistricts resulted from PCA and factors extraction as input data. Through PCA-SOM coupling model, this paper brings about the spatial classification and description of urban internal industrial function structure. Then the following conclusions are drawn. (1) The industrial functions of subdistricts can be represented through extracting the factors of enterprises spatial distribution data by principal component analysis. (2) PCA-SOM coupling model divides Shenzhen’s industrial spatial function into 6 type-zones. In this way the classification results accord with the actual situation and avoid subjective and arbitrary assessment. (3) Shenzhen’s industrial structure presents spatial differentiation in inner city. Unlike concentric ring model of traditional city, Shenzhen’s city center locates at the bottom of geographic space. Moreover the industrial spatial structure of Shenzhen takes clustered modern service industry as the core, spreads as fan-shaped radiation from south to north area on the whole, and has obvious path dependence characteristics. (4) The industrial spatial function of eastern division in Shenzhen is still indistinct, which means further industrial spatial structure planning and more policy support should be implemented on that region in order to develop polycentric industrial radiation mode.

Key words: urban structure, industrial function, principal component analysis, SOM clustering, Shenzhen