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.
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Received: 4 April 2001 / Accepted: 17 November 2001
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Huang, Y., Leung, Y. Analysing regional industrialisation in Jiangsu province using geographically weighted regression. J Geograph Syst 4, 233–249 (2002). https://doi.org/10.1007/s101090200081
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DOI: https://doi.org/10.1007/s101090200081