AURIN has partnered with UNSW Research Infrastructure and FrontierSI, working in collaboration with NSW Spatial Services, Data61, QLD DNRME and Astrolabe, to deliver the Liveable City Digital Twin project. Recognizing that there is an overall lack of comprehensive, federated built environment data, AURIN, along with our collaborators, is proud to contribute to the development of this leading-edge capability.
Urban digital twins provide a virtual representation of our built environment. Using data analytics and simulation models that can be updated and changed in real-time as their physical equivalents change, urban digital twins help us to better plan, design and manage our cities and towns to ensure our communities are resilient to challenges. Planners and policy makers can test scenarios and assess policy or planning impacts on the liveability of the urban landscape through the framework of a digital twin.
Image: The Liveable City Digital Twin interface showing 3D building data.
The Liveable City Digital Twin project is a precinct-level, analytics-aided and standards-based 3D/4D Digital Twin in Western Sydney focused on urban liveability and climate adaptability use cases.
Western Sydney was chosen as our pilot location as it is a typical example of Australian peri-urban areas where development and population increases are outpacing rigorous research to provide an evidence base for planning and policy decision making. The digital twin offers an immediate medium through which we can model scenarios based on policy and development choices to ensure the urban environment we create serves the population that lives there.
“For the project, we focussed on implementing algorithms for real time shadow analysis within the built environment. Developing accurate 3-D terrain and foundation spatial datasets was critical to ensure that the outputs of these algorithms are robust so that they can positively support informed decision making.” – Lachlan Ng, AURIN Data Engineer.
Through this collaboration we have developed 3D representation of the terrain and built environment for the digital twin of the study area. The framework and method we have developed can be applied to other urban areas.
What happens next?
Our next steps will be to develop algorithms for spatial analytics for real-time data. The team will also conduct reviews of the digital twin and take recommendations from the user community. This feedback will inform our strategy for a larger scale digital twin.