1,545
Views
8
CrossRef citations to date
0
Altmetric
Research Article

Decoupling Growth from Growth-dependent Planning Paradigms: Contesting Prevailing Urban Renewal Futures in Sydney, Australia

ORCID Icon, ORCID Icon & ORCID Icon
Pages 321-337 | Received 23 Jan 2020, Accepted 10 Jul 2020, Published online: 13 Aug 2020
 

ABSTRACT

With the population of Sydney expected to reach 7 million+ in the next 20 years, current strategic planning policy is firmly growth oriented in its aims, and growth dependent in its settings, with a key focus on promoting higher density redevelopment around rail stations through value uplift. Using the Sydenham-to-Bankstown Corridor as our case study, this paper engages with the contradictions underpinning current templates for market-driven urban renewal. Questioning models privileging a financialised, hypertrophic reconfiguration of existing neighbourhoods, we examine the business of densification and its spatial manifestation(s) to explore potential frameworks for greater inclusivity in both the process, and outcomes, of suburban growth.

摘要:

随着悉尼人口在未来20年内预计将达到700万以上,目前的战略规划政策的目标是坚定地以增长为导向,并在其环境中依赖增长,重点是通过价值提升促进火车站周围更高密度的再开发. 本文以西德纳姆-班克斯敦走廊为例,探讨了当前市场驱动的城市更新模式所存在的矛盾. 在质疑现有街区金融化、过度重组的模式时,我们研究了密集化的业务及其空间表现形式,以探索郊区发展过程和结果中更大包容性的潜在框架

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Australian Research Council [DP190102762].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 257.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.