Case Study
November 16, 2020
A virtual clone of Adelaide for digital twin and smart city applications
Aerometrex creates a 3D model of the entire city of Adelaide, using a combination of photogrammetry data captured via helicopters and real-time archviz tool Twinmotion.Image courtesy of Aerometrex Ltd.
The year is 2050, and the world’s population is approaching 10 billion. Around 70 percent of this booming population—6.7 billion people—live in urban areas.
People play video games in VR as autonomous vehicles transport them around megacities. Cars, houses, and digital devices are in constant communication thanks to the Internet of Things (IoT). And real-time digital twins enable us to monitor the structural health of physical buildings, fixing things before they break for safer, more resilient infrastructure.
It might sound some time away, but if you think about how much smarter homes have become over just the last five years, with intelligent devices like smart thermostats, smart speakers, and smart light bulbs, all this could be closer than you think.
Technology is developing at a hurtling pace, which means the cities of the near future could look markedly different from today. When it comes to designing and planning these cities—as well as helping to manage them through the visualization of IoT data—real-time technology is set to play a big part.
People play video games in VR as autonomous vehicles transport them around megacities. Cars, houses, and digital devices are in constant communication thanks to the Internet of Things (IoT). And real-time digital twins enable us to monitor the structural health of physical buildings, fixing things before they break for safer, more resilient infrastructure.
It might sound some time away, but if you think about how much smarter homes have become over just the last five years, with intelligent devices like smart thermostats, smart speakers, and smart light bulbs, all this could be closer than you think.
Technology is developing at a hurtling pace, which means the cities of the near future could look markedly different from today. When it comes to designing and planning these cities—as well as helping to manage them through the visualization of IoT data—real-time technology is set to play a big part.
Aerometrex is one of the companies at the forefront of smart city development. It specializes in aerial imaging and mapping, creating 3D models of urban areas that are used in the development of digital twins and smart city applications.
The firm has been putting real-time architectural visualization tool Twinmotion through its paces, creating a 3D model of Adelaide and the area surrounding it—around 1000 sq km—using photogrammetry data captured via fixed-wing aircrafts and helicopters.
The firm has been putting real-time architectural visualization tool Twinmotion through its paces, creating a 3D model of Adelaide and the area surrounding it—around 1000 sq km—using photogrammetry data captured via fixed-wing aircrafts and helicopters.
Digital twins and smart cities
Fabrice Marre is the geospatial innovation manager who heads up the R&D team at Aerometrex. His role involves keeping up with existing and emerging 3D visualization technologies within the geospatial industry and beyond.Marre has been using Unreal Engine for years, leveraging the technology’s photorealistic rendering to showcase 3D models generated from photogrammetry in the most engaging and realistic way possible. “The visual quality of Unreal Engine is exceptional, but it takes some experience to produce high-quality content quickly for very large assets,” he says.
When Marre heard that Epic Games, makers of Unreal Engine, had joined forces with Twinmotion, a fast and easy-to-use archviz tool, his interest was piqued. He was particularly intrigued by the possibility of designing a complex environment in real time, with the potential to go back and forward to iterate and produce results quickly. “It was just a question of time until we tried it with our own large-scale 3D data,” he says.
He got his chance with Aerometrex’ yearly internal capture program, which aims to capture and generate large-scale 3D city models of all the major cities in Australia. Those 3D city models are used as foundation data for digital twins and smart cities applications. New constructions or building design can be integrated into the 3D models and used for community consultation, engineering work, planning, solar simulation, and assessing lines of sight.
He got his chance with Aerometrex’ yearly internal capture program, which aims to capture and generate large-scale 3D city models of all the major cities in Australia. Those 3D city models are used as foundation data for digital twins and smart cities applications. New constructions or building design can be integrated into the 3D models and used for community consultation, engineering work, planning, solar simulation, and assessing lines of sight.
Photogrammetry capture and real-time visualization
Aerometrex delivers 3D models that are captured using aerial photogrammetry techniques. Using a large format camera attached to a fixed-wing aircraft, Marre and his team captured and generated a large-scale 3D model of Adelaide, where the company is headquartered, and its surrounding area. They also captured and produced a 3D city model of the central business district (CBD) area at a higher resolution from a helicopter platform.The 3D models generated then went through a manual clean-up process to remove any geometry and texture artifacts. These models were split into tiles with different levels of detail and exported in many 3D formats including OBJ and FBX. To integrate the 3D city models into Twinmotion, the team produced multiple objects made of merged OBJ tiles and then used tiles at lower levels of detail the further they were from the focus area.
The team dragged and dropped assets from Twinmotion’s library to populate the city model. These were complemented by Quixel Megascans assets and purchased assets. “I’m blown away by the exceptional realism and quality of the lighting, particles, and atmospheric effects—and how much life can be so easily added to a static 3D city model with the huge Twinmotion asset library available,” says Marre.
Real-time technology provided a super-fast feedback loop in the creative process, enabling Marre to quickly modify and enhance a 3D city model and see results in real time. “We’ve demonstrated that we can work with very large 3D datasets and have started producing videos using Twinmotion for all our latest 3D projects,” he says. “Twinmotion has become part of our workflow, both from a project and marketing point of view.”
Real-time technology provided a super-fast feedback loop in the creative process, enabling Marre to quickly modify and enhance a 3D city model and see results in real time. “We’ve demonstrated that we can work with very large 3D datasets and have started producing videos using Twinmotion for all our latest 3D projects,” he says. “Twinmotion has become part of our workflow, both from a project and marketing point of view.”
I’m blown away by the exceptional realism and quality of the lighting, particles, and atmospheric effects—and how much life can be so easily added to a static 3D city model with the huge Twinmotion asset library available. "
Fabrice Marre
Geospatial Innovation ManagerA strategy to handle city-scale projects
Up to now, Twinmotion has generally been used to create smaller projects than this. A large project might include visualizing a football stadium or part of a housing estate. As Aerometrex has shown, the tool has the capability to visualize environments on a far grander scale.That said, an endeavor as ambitious as visualizing an entire city does come with its own set of challenges. “Clear data management and asset production strategy, as well as a good understanding of the limit of the workstation, are essential when dealing with very large datasets,” explains Marre. “A large 3D model cannot be loaded at once. Splitting, merging, and decimating the data into manageable assets is the key.”
A huge city environment results in a hefty 3D model. Having strategies in place to ease the load on your workstation is essential. “Twinmotion does not currently support dynamic loading of level of detail, so in the case of Adelaide, we used high-resolution 3D model tiles over the CBD and merged them together,” says Marre. “We then merged a ring of low-resolution tiles around the CBD and used lower level of detail tiles the further away we are from the CBD.”
The team also manually hid the individual blocks of the 3D models that were not visible from a specific point of view to free up RAM and improve the real-time experience.
The success of the project has secured Twinmotion a permanent place in the Aerometrex pipeline. “Features such as drag-and-drop functionality, texture management, an extensive realistic asset library, customizable vegetation assets, and environment settings make the process of producing photorealistic visuals easy,” explains Marre. “All these benefits, in my view, place Twinmotion ahead of the pack.”
Marre says that Twinmotion will stay as their tool of choice for producing high-quality videos quickly and easily, while Unreal Engine will be dedicated to more advanced applications, including interacting with assets and developing interactive VR experiences. “It’s great to see real-time technology becoming a force for innovation across industries,” he says. “It’s very exciting for me to add a bit of the geospatial industry to the mix.”
The success of the project has secured Twinmotion a permanent place in the Aerometrex pipeline. “Features such as drag-and-drop functionality, texture management, an extensive realistic asset library, customizable vegetation assets, and environment settings make the process of producing photorealistic visuals easy,” explains Marre. “All these benefits, in my view, place Twinmotion ahead of the pack.”
Marre says that Twinmotion will stay as their tool of choice for producing high-quality videos quickly and easily, while Unreal Engine will be dedicated to more advanced applications, including interacting with assets and developing interactive VR experiences. “It’s great to see real-time technology becoming a force for innovation across industries,” he says. “It’s very exciting for me to add a bit of the geospatial industry to the mix.”
It’s great to see real-time technology becoming a force for innovation across industries.
Fabrice Marre
Geospatial Innovation Manager Developing the smart cities of the future
The smart cities of tomorrow will be built on the datasets of today. Their foundations will be digital as much as physical, with large-scale city environments designed and managed using real-time visualization. “These real-time environments provide an accurate base to develop designs, test scenarios, and communicate a clear vision of what a future city could look like,” says Marre.Interactive 3D is a universal language. It provides the tools to quickly test complex hypotheses, dynamically change lighting and weather conditions, add life to a static model, and produce realistic visualization.
While architecture and urban design concepts can be visualized on their own over a limited space, large-scale city environments can add context to a project and stimulate thinking outside the box. Large contextual 3D data enables us to not only focus on a design, but also to simulate how a design will fit in its environment in a realistic way.
Image courtesy of Aerometrex
With the Adelaide project, Aerometrex has discovered a new, fast option for creating city-scale visualization. “Twinmotion is an amazing tool and I believe it should not be restricted to small environments,” says Marre. “It has the capability to load very large datasets, provide solutions for large-scale design visualization, and expand into new markets.”
For those of us intrigued about the urban spaces of the future, Aerometrex provides a fascinating glimpse into the large-scale environment datasets that will inform their development.
For those of us intrigued about the urban spaces of the future, Aerometrex provides a fascinating glimpse into the large-scale environment datasets that will inform their development.