Analysing regional industrialisation in Jiangsu province using geographically weighted regression |
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| Authors: | Yefang Huang Yee Leung |
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| Institution: | (1) Department of Geography and Resource Management, Center for Environmental Policy and Resource Management, Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, Hong Kong (e-mail: Lucy-huang@cuhk.edu.hk, Yeeleung@cuhk.edu.hk), HK |
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| Abstract: | Industry is the most important sector in the Chinese economy. To identify the spatial interaction between the level of regional
industrialisation and various factors, this paper takes Jiangsu province of China as a case study. To unravel the existence
of spatial nonstationarity, geographically weighted regression (GWR) is employed in this article. Conventional regression
analysis can only produce `average' and `global' parameter estimates rather than `local' parameter estimates which vary over
space in some spatial systems. Geographically weighted regression (GWR), on the other hand, is a relatively simple, but useful
new technique for the analysis of spatial nonstationarity. Using the GWR technique to study regional industrialisation in
Jiangsu province, it is found that there is a significant difference between the ordinary linear regression (OLR) and GWR
models. The relationships between the level of regional industrialisation and various factors show considerable spatial variability.
Received: 4 April 2001 / Accepted: 17 November 2001 |
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| Keywords: | : Geographically weighted regression industrialisation Jiangsu spatial nonstationarity |
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