Want to know the fastest way to get from Singapore’s luxurious Marina Bay Sands to Sentosa Cove on the city/state’s playground of Sentosa Island?

Whilst Google Maps would be an option, Singapore’s Onemap site enables you to use real-time data to identify and evaluate options involving, train, bus, car, cycling and walking. For instance, going by car via the fastest route down Telok Blangah Road would take approximately 17 minutes. Those wanting exercise should allow 1 hour and 6 minutes for a 10.8-kilometre cycle.

As well, the software will give you a map of nearby amenities, land ownership details, schools and rental property transitions – all delivered in an open source environment.

This has been available for several years but is only the start of Singapore’s transformation toward becoming a ‘smart city’ using mapping and data, explained Singapore Land Authority chief executive Tan Boon Kai at the Year in Infrastructure conference hosted by Bentley Systems late last year in Singapore.

In 2013, the country commenced a 3D mapping initiative led by the Singapore Land Authority in conjunction with the water utility and air traffic control to create accurate 3D models both above and under-ground. The first phase of this project was completed in 2015. The second, which involves capturing data at street level, was completed early last year. The next phase is ‘build’ the entirety of Singapore in a digital built environment – a project which will be known as Virtual Singapore.

Already, agencies are using the models which are developed and in progress for tasks such as planning and development, flight risk mapping and managing and measuring urban heat and airflow levels. Data captured from high resolution laser scanning using cloud based terrestrial scanners has enabled 3D modelling of city properties for heritage documentation purposes. Massive amounts of street level data covers more than 6,000 kilometres of Singaporean roads. All this, overlaid with a satellite positioning reference network, will help to enable autonomous vehicles or self-driving cars to be managed via an overarching network.

In short, Singapore is building a 3D model and map of its entire city. Its goal is to improve life for citizens, generate opportunities to boost economic development and productivity and build stronger communities for its people.

All this, essentially, is known as context capture and reality modelling: the use of imagery uploaded through iPhones, drones or even planes for processing by modelling software to create a model of ‘reality’ for a property, project piece of infrastructure, localised area or an entire city.

In a joint interview late last year, Bentley Systems senior director of portfolio development Francois Valois and vice president – ANZ Brian Middleton said opportunities both around the world and in Australia is significant.

At a city level, Valois says you can use models of entire metro areas to analyse issues such as vulnerability to flooding through flooding simulation or to urban heat across metropolitan areas. This would enable greater effectiveness in devising flood mitigation strategies or attempting to avoid high concentrations of elderly or vulnerable people in areas of significant extreme temperature sensitivity.

More locally, he says, reality modelling and imagery can be used to plan construction or assess project progress.

In Australia, Middleton said Bentley is working with several councils to use reality modelling to help mitigate coastal erosion. By taking a model of the coastline as it normally stands and another after a severe weather event, councils can understand the impact of the event upon coastal erosion and can identify parts of the coast which may be subject to further erosion and require protection.

The company is also working with state police forces under arrangement whereby drones could be sent up at short notice to obtain imagery of scenes of crime or fatal incidents. Uploading this into a reality model could help police to reconstruct environments relating to the scene.

Naturally, there are privacy and security challenges.

Valois says these can be managed. On security, he says information can be processed in private servers or public or private clouds. As for privacy, he says the software can blur or eliminate moving objects such as people or cars. Whilst avoiding the unintentional inclusion of private property in captured images is difficult, he says areas of unwanted imagery can be blotted out during processing.

Australia has opportunities through digital mapping and reality modelling.

Should we capitalise on these, benefits could be significant.