A fine-grained investigation on the predictors of urban green space growth in Nanjing

Existing studies have primarily examined urban green space (UGS) evolution in isolation from the urban development context, neglecting the dynamicity of the factors affecting UGS growth in different spatiotemporal conditions and urban development levels. Taking Nanjing as the study site, we constructed spatial lag models using multi-source data and investigated the patterns and predictors of UGS growth across diverse spatiotemporal conditions in high-density environments. The model results show that: (1) although good natural conditions can support UGS development, this effect is greatly weakened in fast urban expansion as other land uses show higher priority in land occupation; (2) industrial and public service lands and commercial lands show a negative effect on UGS growth in the early and late urbanization, respectively, while residential lands demonstrated sustained negative effect in all the urbanization phases; (3) the effect of the total population and population structure varies in different urban development phases; (4) at an advanced urban development level, the areas close to city centre have better opportunities to install new UGSs. These findings offer useful references to the decision makers and planners, especially for their work on the UGS layout optimization within the high-density areas.