Australia's cities face significant social, economic and environmental challenges, driven by population growth and rapid urbanisation. The pressure to increase housing availability will lead to greater levels of high-density and medium-density stock. However, there is enormous political and community pushback against this. One way to address this challenge is to encourage medium-density living solutions through "precinct" scale development. Precinct-scale development has the potential to include additional hard and soft infrastructure that may offset the perceived negativities of higher densities. As part of Australian research into precinct-scale development, and as part of our broader Smart Cities approach, or more specifically City Analytics approach, new digital planning tools - Envision and ESP - have been developed to support scenario planning and design needs. They utilise a data-driven and scenario planning approach underpinned by Geographic Information System (GIS) functionality. We focus on a case study in the City of Blacktown, Western Sydney, New South Wales, Australia. By 2036 Blacktown is forecast to grow to approximately 500,000 people (an increase of over 30%) and 180,000 dwellings. Most new dwellings will be delivered through urban infill. The Blacktown master plan promotes higher density housing, mixed employment uses and continued improvements to the public domain. Our study provides a unique opportunity to implement this broad strategy within a specific case and location. Specifically, this paper provides information on how these digital planning tools supported Blacktown planners in identifying, co-designing and implementing a new approach for precinct level planning. It also presents the results of an evaluation of digital-planning tools in the context of the Blacktown case study.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives Volume 42, Issue 4: 3rd International Conference on Smart Data and Smart Cities, SDSC 2018
Conference name
3rd International Conference on Smart Data and Smart Cities, SDSC 2018