Papers
Parasite City
Guoyi Chen University of Technology Sydney
Seungcheol Choi University of Technology Sydney
Mohammed Makki University of Technology Sydney
Jordan Mathers SJB
Parasite City The Suburb of Alexandria in Sydney: Retaining the industrial district as an integral part of the suburb’s urban regeneration In the context of rapid urbanisation and exponentially increasing population numbers; the stresses imposed on existing cities to sustain this demand is ever-growing. Although many new cities are being developed worldwide, it is the existing cities that are faced with the challenge of accommodating increased density within a finite space. One such city is Sydney, with a population expected to grow by 30% in the next 25 years; the city’s suburbs are going through a continuous cycle of urban regeneration, in which the old is replaced with the new. Although much of this regeneration is through the development of mid to high-rise apartment towers in place of townhouses; one part of the city, the suburb of Alexandria, houses the industrial district that has existed for generations, historically serving as one of the city’s largest industrial centres due to its proximity to the airport and the central business district. The ‘Inner city redevelopment plan’ by the City of Sydney aims for the major re-development of several inner-city suburbs in Sydney, one of which is Alexandria, towards high-density residential suburbs over the next 30 years. Inevitably, to meet the demands for residential developments, Alexandria is threatened from going through a gentrification process, in which the industrial districts that have existed for the past century are to be erased to pave the way for new builds. The research presented in this paper proposes an alternative urban regeneration strategy for the suburb of Alexandria that aims to retain the existing industrial district, minimise demolition and redevelopment within the site, and seek a sustainable way to allow the suburb to support growing numbers in the population. Through the application of an evolutionary generative process, the paper proposes an urban growth strategy that maintains the urban structure of the existing, and uses it as a basis for the development of new mixed-use typologies that ‘parasitically’ integrate within the suburb’s existing morphology. The paper also builds on recent research for the application of sequential evolutionary simulations to tackle complex design problems comprised of a high number of fitness objectives. The simulations address issues of network and spatial organisation (relying on the syntactic analysis), followed by the morphological distribution and relationships of various mixed-use typologies that leverage the existing urban fabric as the basis for the regeneration strategy. The paper’s results examine an alternative approach to the City of Sydney’s current plans for urban regeneration; in which the redevelopment for the purposes of accommodating a growing population is addressed through a model that utilises the existing fabric as an integral part of the regeneration process, not one that must be demolished or erased. References: Batty, M. (2013) The New Science of Cities, Cambridge, Mass., The MIT Press. Hawken, S. and Hoon Han, J. (2017) ‘Innovation districts and urban heterogeneity: 3D mapping of industry mix in downtown Sydney’, Journal of Urban Design, Routledge, vol. 22, no. 5, pp. 568–590 Hillier, B. and Hanson, J. (1984) The Social Logic of Space, Cambridge University Press. Makki, M., Showkatbakhsh, M., Tabony, A. and Weinstock, M. (2018) ‘Evolutionary Algorithms for Generating Urban Morphology: Variations and Multiple Objectives’, International Journal of Architectural Computing, vol. 17, no. 1, pp. 5–35 Randall, M. (2020) ‘The Taikoo Shing Superblock: Addressing urban stresses through sequential evolutionary simulations’, D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), Proceedings of the 25th CAADRIA Conference – Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 415-424
Keywords: Gentrification | Urban Regeneration | Sequential Evolutionary Simulation | Sustainability