Multi-criteria methods for the optimal localization of urban green areas

With reference to the important issues on sustainable urban development, ecosystem services play a significant role today, able to significantly affect the quality of life in cities. In this perspective, urban regeneration processes must be encouraged through the creation of green areas. Such intervention strategies enhance the livability and resilience of growing cities by: (i) generating ecosystem services (ESs); (ii) containing the negative impacts of urbanization; and (iii) contributing to a Circular Economy (CE). This study uses techniques of multi-criteria evaluation with to characterize a methodology that can favor the best localization of urban parks. Elements of novelty of the research concern both the logical structure of the implemented algorithms, based on a panel of rigorously selected indicators, and the consistency checks between the different methods examined. Specifically, we propose a set of six indicators of general validity and easy to estimate, with aim to define: (i) a methodology easily replicable to different socio-economic contexts; (ii) a useful tool for decision-makers and urban planners as they are easy to be practically implemented. Once indicators are selected, we implement and compare four different evaluation approaches – AHP, ELECTRE, TOPSIS and VIKOR – to select the optimal localization of a green areas in an Italian city. The goal is to provide a more cohesive framework for the evaluation of the optimal location of urban green strategies, in the light of economic, environmental, and social criteria. •The optimal localization of green areas in the city maximizes ecosystem services for the community•The correct use of urban land requires multi-criteria decision-making approaches•The multi-criteria techniques guide towards achieving the goals of the Circular Economy•This research tests the effectiveness of an innovative multi-criteria evaluation protocol•The results of the analysis have significant implications in terms of Economic Policy