A method for influencing residential land population density by industrial development considering global and local scales: A case study of Wuzhong city, China

Abstract

Residential land population density (RLPD) reflects the actual distribution of urban population. The types of industry directly affect people’s residential choices. However, few studies have recorded the impacts of different industries on RLPD. This study developed a multi-scale approach framework for the impact of industrial development on RLPD by using spatial correlation network model, spatial econometric models and geographically weighted regression model. We selected 11 industries and calculated their economic development and employment levels respectively, resulting in 22 explanatory variables. At the global scale, there were significant spatial associations between the eleven industries and RLPD by comparing their spatial networks. The impacts of catering industry, accommodation industry, and general equipment manufacturing industry from an economic development perspective on RLPD were negative, while other eleven significant variables were positive. The improvement of the industry level accelerated the clustering of urban population, while high-end catering and accommodation industries were built away from dense crowds. At the local scale, there were variable impacts spatially on RLPD, and the positive impacts gradually increased from the city center outwards in most industries. Better living environments increased people’s confidence in residential choices. We further discussed the fine-scale urban land layout by six typical examples and proposed strategies for integrating industry and residence. Our conclusions proved that the multi-scale modeling framework proposed in this study effectively explained the impact of industrial development on RLPD.