Spatial digital twins combine data, 3D modelling and geospatial software to digitally represent buildings, neighbourhoods, precincts, towns and cities; sometimes even entire regions. First conceptualised in the early 2000s, digital twins are now being used in earnest as a planning tool across the built environment.
Digital twins are a growth industry, set to play an important role in the development of smart cities. According to a report by the World Geospatial Industry Council, the digital twin market will be worth an estimated USD$25 billion by 2026.
These incredible digital replicas of the real-world let users immerse themselves in everything from a place’s geographic layout and natural landscapes to buildings, structures, assets, transport links and critical infrastructure services.
Spatial digital twins are an example of what are known as data centric digital twins - where data informs the development of the twin. Data gets piped in from multiple third-party datasets and could include environmental, digital engineering, utilities and sensor information. Social and economic data on the movement of people and goods can even be included. The possibilities for making great use of data are limitless.
There’s lots of benefits. Location-based insights provided by spatial digital twins can help city planners better understand urban policy issues, test potential interventions and deliver more sustainable planning and development. But only if the twin has been properly designed and developed, with consideration given to the all-important role of data.
Beware digital duds
It can be tempting to create a digital twin and feed it some data later. This is a risky way of going about things. Treating data as an afterthought will create problems down the line.
Without first thinking about the data, your digital replica of the ‘real world’ will amount to little more than a husk with minimal practical value. You won’t be able to use your twin to see how a proposed new infrastructure development, for instance, will slot into the here and now of the urban form.
Why? Because the built environment (and its data) is always changing. Spatial digital twins developed with data uploaded after the fact quickly get outdated. All you’ve succeeded in doing is creating a ‘point in time’ twin that will be cumbersome to update and maintain. Its value will continue to degrade over time.
Take a data-first approach
Data is the engine that drives digital twins. It’s where the true value of your twin lies, not in the bells and whistles of its flashy visuals and user interfaces.
When you access data through a spatial digital twin, you're accessing it direct from its custodian. As digital engineers, we set up systems to standardise and let the twin tap into many sources of data. With data standards varying across industries and jurisdictions, this isn’t always a quick or easy process but is worth it in the long run.
In a well set up spatial digital twin, users can query data on all kinds of objects to discover layers of information beyond the twin’s geographic surface features. Feed it with the latest waste management data, for example, and you can not only see the locations of city rubbish bins, but when they were installed and last serviced.
Designed to handle constantly changing feeds of information, spatial digital twins provide a window into past, present and future. They can be set up in a way that let users examine historic and projected data. This is a boon for planners wanting to understand how a planned built development compares with days of old or may impact future urban form.
Learn from the best
One of the best local examples of a spatial digital twin is the virtual replica being developed for the State of New South Wales (NSW). Digital experts from WSP are heavily involved in this AUD$40 million project,. as well as a digital twin for the State of Victoria.
Put together with the input of public and private sector organisations, the NSW twin combines data sources from across the state - including spatial, natural resources and planning information. This is all integrated with real-time feeds from sensors.
It can be used by anyone to visualise location information in a 3D or 4D model of the real-world - in near real time. That supports improved decision making, and planning, operation and design of assets and services. Data in the NSW twin is even being used to inform risk and resilience decisions in the location and protection of essential utilities infrastructure in emergency situations like bushfires.
Much of the upfront development focus with the NSW twin was on bringing in clean and consistent data. Being consistent around how data gets pulled into and out of the twin has been a boon for accessibility. It makes the twin better able to be queried, and lets users harness the full power of the twin to solve complex real-world challenges.
Setting rigorous data standards at the outset has set NSW up for success and won plaudits from users. In the twelve months to December 2021, the twin received 18 million requests for access to 3D datasets.
Now, more than ever before, the world is awash with data on the physical and built environment. Bringing these zeros and ones together in a single place where they can be visualised, interpreted and analysed is the great value-add of a spatial digital twin.
Ultimately, spatial digital twins contribute to developing better designed, more sustainable and resilient communities – from the smallest of assets in the built environment to entire cities or regions. But this can only happen if data sits at the heart of your efforts. Otherwise, as Shakespeare’s mad old king reminds us, ‘Nothing will come of nothing’.