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Abstract
In recent years, the planning, design and installation of “green infrastructure” at the local and city level has been identified as a best practice and nature-based solution to achieving greater urban sustainability and resilience. It is a component of the international urban movement “Smart Cities”. Green infrastructure is an integrated multi-scale network of green spaces within, beyond, and around a city. It provides many benefits - most importantly ecosystem services for human and environmental health.
This study aims to develop an indicator-based model using a mixed-method approach as a means to evaluate the performance of urban green infrastructure. This model is composed of a set of sixteen key indicators within four subcategories: ecological; health and well-being; sociocultural; and economic. Each represents key interactions between human health, ecosystem services and ecosystem health. The proposed performance indicators are based on the incorporation of results in three systematic, mixed-method approaches that consist of the development of the Drivers-Pressure-State-Impact-Responses (DPSIR) model specific to this research problem. The DPSIR model is a conceptual foundation to govern the development of sustainability indicators. Semi-structured interviews are undertaken involving twenty-one selected Australian experts, and input from 373 Australian national and international stakeholders from representative fields via an online questionnaire. An assessment matrix is developed that comprises description, calculation (equation) and units for each individual indicator. This model is tested, validated and verified through a case study in Sydney, Australia.
The significance of the research is that: the proposed indicator-based model provides an opportunity to understand the complex relationships of the multidimensional structure of urban green spaces; it serves as a useful insight for urban designers and decision-makers in monitoring various aspects of the urban ecosystem; and it also allows for early warnings regarding any undesirable changes in sustainability levels.