Fine-scale mapping of urban ecosystem service demand in a metropolitan context: a population-income-environmental perspective

Abstract Scientifically characterizing demand for urban ecosystem services (ESs), particularly in a metropolitan context, plays a key role in the optimal allocation of urban ecological resources. However, the definition of urban ES demand is still in the fuzzy conceptual stage. Therefore, this study proposed a conceptual framework for fine-scale mapping of urban ES demands from the perspective of population-income-environmental pressure/preference (PIEP). By integrating multi-source data, the framework was implemented in a metropolitan city of China, Hangzhou, focusing on demands for five exemplary urban ESs, i.e. cooling, air purification, noise reduction, carbon sequestration, and outdoor recreation. The principal component analysis (PCA) was applied to dimensionality reduction and a comprehensively assessment of multiple ES demands. ES demand bundles were identified based on the k-means cluster analysis, where a hierarchical elbow method was devised for setting an optimal cluster number supported by practical decisions. The results showed that the demand for regulating services had more significant spatial aggregation characteristics than that for cultural services. Moreover, the high demand areas were concentrated in the city center and two sub-centers, while demand gradually decreased towards the urban periphery. The ES demand bundles presented three major patterns of composite modes: the multi-demand synergy type, regulating-cultural demand trade-off type, and local-based type. Our findings suggest that the PIEP framework is a promising decision-support tool which can tease out urban ES demands for urban planning and sustainable development.