Significant differences in urban greening have occurred in Chinese cities, accompanied by China's rapid urbanization. However, there are relatively few studies on the spatial differentiation of urban greening in China at the city level. In addition, there is no unanimous conclusion on the main factors influencing the spatial differentiation of urban greening. Based on 2014 emission inventory data from 289 cities, the spatial differentiation pattern and spatial correlation characteristics of the urban green space ratio, urban green coverage rate, and public green area per capita were calculated and analyzed using global and local Moran's I. We then used ordinary least squares, spatial error model, spatial autoregression, and geographically weighted regression to quantify the impact and spatial variations of China's economy on urban greening. The results showed (1) a significant spatial dependence and heterogeneity existed in urban greening values, and the patterns showed influences of both the stage of economic development and spatial agglomeration; (2) regression models revealed per capita GDP had a positive effect on the urban green space ratio and public green area per capita while the urbanization rate, secondary industry, urban land, and population density had opposite effects on these two greening indexes; and (3) geographically weighted regression revealed per capita GDP had a greater influence on urban greening in the northwestern region than in the southeastern region. The study could constitute a valuable reference for mid-to-long-term green space planning policy in diverse parts of China and could further assist in coordinating the development of urban greening and economic growth.
Keywords: China; Economic growth; Geographically weighted regression; Spatial variation; Urban environment; Urban greening.