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The Hort Innovation Green Cities project “Measuring Australia’s Green Space Asset” (MUGS) undertook a global review of urban green space (UGS) measurement research and engaged with Australian stakeholders to gauge current practice.
The overall aim of the project was to foster best-practice UGS planning and management by juxtaposing the scientific state of the art with the contextualised needs expressed by potential Australian end users. The synthesis of findings informed a ‘blueprint’ which sketches the contours of a possible nationally consistent UGS decision-support framework. The framework is illustrated with a worked example from Australia (rapid assessment of urban green space assets using satellite imagery).
Through extensive stakeholder engagement by means of 15 interviews and 5 Focus Groups across Australia we identified strong interest in a nationally consistent UGS decision-support framework. Stakeholder research also found that currently used UGS measures matched the broad thematic grouping of UGS measures found in literature.
When synthesising findings these thematic groupings were consolidated in five thematic groups: 1) Human Wellbeing & Liveability; 2) Ecosystem Management; 3) Vegetation Management; 4) Asset Management; and 5) Urban Planning.
When current Australian use of UGS measures is compared with the scientific state of the art it can be seen that only a fraction of available measures and associated methods are currently being used. Particularly Human Wellbeing & Liveability measures were under-represented.
The review of scientific literature found two overarching themes: the measurement of bio-physical UGS; and the measurement of the performance of UGS. Measurement of bio-physical characteristics of green space is particularly important when benchmarking the character of an area under investigation. Bio-physical measures capture such UGS characteristics as: number of trees; tree canopy; number of parks; and size of green space. Bio-physical green space measures provide raw indicators of green space and can be used to inform further metrics. A performance perspective on green space measurement requires defining what performance is. For example, green space can be measured with consideration to biodiversity potential, ecosystem service provision, or recreation benefits. Measuring green space in this way provides more comprehensive assessment of UGS. However, performance-based measures can be more complex to calculate and typically require biophysical measures. Oftentimes both bio-physical and performance-based UGS measures are necessary.
The project was centred on the notion of “tools”. As there are alternate conceptions of what constitutes a tool it was found that definitional clarity was required before a synthesis of findings could inform the blueprint. Two definitions, as broadly found in literature, were adopted: “soft” tools and “hard” tools. Soft tools are documented/published methodologies of analysis. Hard tools are codified methodologies or software implementations of such methodologies. The project established a catalogue of hard (12x) and soft (6x) tools, each of which was characterised in terms of their ability to map, monitor and report on UGS. The 18 tools were subsequently screened for their potential suitability in the Australian context, and any required modifications were documented. The catalogue of tools is presented below. Based on findings from stakeholder engagement and literature review, an Australian decision-support framework for best practice UGS planning and management was conceptualised. This reflects an explicit distinction between (existing) analytical tools - both “soft” methodologies and “hard” software implementations - and a (novel) decision-making framework.
The blueprint employed a storyboard design with six panels, each conveying a key message outlining features of the decision-support framework: 1) growing towards best practice planning and management in Australia; 2) decisions have a variety of entry points; 3) measures are grouped thematically; 4) analytical tools range from published methods to coded software; 5) these elements can be brought together in a decision-support framework; and 6) an example of how the decision-support framework may be used.
Our findings suggest that a nationally consistent decision-making framework would have strong innovative potential and would stand a high chance of adoption as there is strong demand. A business case would need to be developed to assess the feasibility of implementation.