Abstract
With an increasing global urbanization, demands on the livelihood of cities are rising swiftly. In the conventional urban growth, biodiversity is often constrained, separation of functions leads to inefficient resource use, impact of climate change becomes extreme and human health is increasingly endangered. Green infrastructure (GI, e.g. green roofs, parks) in cities may simultaneously supply multiple functions that contributes to solve these issues. The challenge is how to accommodate and harmonise these possibly synergising or competing functions of GI in current and future urban landscape. Here, transdisciplinary learning[14] will be used to co-create the planning and design of the multi-functioning of GI in cities. Building from our experiences in Xiamen, Breda and Nieuwegein, we will develop and evaluate such multi-functional designs for these cities. We hypothesize that learning among multiple disciplines and cities are the two keys to unlock the potential of multi-functioning of GI. In this research we aim at operationalizing this learning process via (1) co-creation of a GI planning and evaluation tool, MultiGreen, to stimulate and distil the transdisciplinary learning for multi-functioning of GI and (2) participatory-based application of MultiGreen in selected case cities to facilitate learning among stakeholders so as cities. We start with, but not limited to, integrating three main GI functions: the circular food provision, climate adaptation, and biodiversity restoration; different GI approaches like urban farm, green roofs or wadi are thus considered. Then, a GIS-based building stock model is connected to an agent-based model to analyse the potential of ecological and social-economic benefits for accommodating different GI approaches. At last, a geo-spatial module matching the GI provision of multi-functioning and local demands will be developed and applied via a participatory approach in different case cities. Thus MultiGreen will enable the future designs of multi-functional GI to maximize the livelihood cities.