Optimizing Spatial Distribution of Urban Green Spaces by Balancing Supply and Demand for Ecosystem Services

The capacity and ecological flows of ecosystem services as well as the demand for them are key areas of urban and rural ecological planning that have been studied using the spatial-explicit model as a decision support tool. This study develops a framework for mapping the relationships among the capacity of and demand for ecosystem services, ecological flows, and planning management. This is done by estimating the ecosystem services based on the space for recreation and environmental conditions and assessing planning for green spaces using the spatial-explicit model. The results show that the carrying capacity of green recreational space was high in the northwest, southwest, and southeast parts of the city of Hefei in China, where this space was highly sustainable in the northwest and southwest. The data also show that the carrying capacity for air purification was higher in the northwest, southwest, and southeast suburbs of Hefei, while areas with high demand for air purification were mainly located in the northeast. The spatial variation in the flows of supply and demand for ecosystem services remained high and unbalanced in the northeast and southwest of Hefei. The excessive use of ecosystem services was concentrated in the urban center while their use in suburban areas was sustainable. The results show that the gap between the supply and demand of space for recreation increased with distance while that between the supply and demand of air purification decreased with increasing distance. The results of assessment based on spatial visualization show that green space was abundant in areas with low demand for it, while those with high demand for it tended to have limited green space in Hefei. This analysis shows that indices for the demand for green spaces in the context of ecosystem services can be improved via public participation, interactions between different scales of ecosystem services for green space, and use of decision support in urban and rural planning systems. These areas will form important directions for future research.