When proposing and reviewing new developments, urban planners, architects and the broader public must make well-informed planning decisions that fit within the broader urban context to foster a sustainable future and avoid costly and unnecessary redevelopment later on. There is often no comprehensive, publicly available and data-based spatiotemporal body of knowledge to help support these decisions. This paper uses the City of Sydney (CoS) as a case study to show how open data about individual development applications (DAs) can be used to build a critical spatiotemporal information framework to fill this gap and guide important city-shaping design and planning decisions. This research proposes a novel and broadly applicable methodology based on Python data analysis and mapping to extract and visualise spatiotemporal insights from DA data in terms of DA lodgement numbers and locations, DA estimated costs, DA proposed land use and application processing times. The results show a consistent decrease in DA lodgement numbers since 2008, likely accentuated by the COVID pandemic since 2020. This is contrasted by a steady increase in the median cost of DAs since 2005. Development hot spots are identified in the Sydney CBD and the suburb of Zetland, whereas the western and central parts of the local government area (LGA) were found to be lodgement cold spots consistent with higher concentration of heritage conservation areas. DAs proposing new uses fall primarily in the retail category, followed by commercial land uses between 2005–2011 and residential uses since 2012. Analysis of DA assessment time showed that 76% of DAs were approved or refused within 3 months, with a positive but limited correlation between estimated cost and assessment time. All charts and maps are made available in an online dashboard.

» Author: Zhiyu Zhu

» Reference: doi: 10.3390/buildings12101601

» Publication Date: 03/10/2022

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