Main image of 3D City Models Accelerate the Creation of Smart Cities and Digital Twins, Data-Driven Efforts in Electronics

3D City Models Accelerate the Creation of Smart Cities and Digital Twins, Data-Driven Efforts in Electronics

Geographic information systems (GIS) visualize geospatial information

GIS stands for “geographic information system,” a system that displays various information on maps for different purposes. Information about events associated with the positional information of a given point or area in space is known as “geospatial information.” For example, population distribution, land values, building attributes, inundation levels during floods, and other information about a given area or point can be color-coded for different purposes. Dynamic information such as the flow of people and goods and meteorological changes can be visualized. Different types of geospatial information can be overlaid. These actions and more make it possible to visualize multiple types of information simultaneously so that the desired information can be understood visually, expediting and enhancing the sophistication of analysis and decision-making. 

GIS can be used for a wide range of purposes, including city planning, hazard maps for disasters, disaster prevention planning, and monitoring infrastructure as well as evaluating accessibility to everything from real property to train stations and analyzing trade areas, which is key for planning new commercial facilities.

GIS services in everyday life include car navigation systems and smartphone map applications that add building information, traffic conditions, and other geospatial information to points and areas on GPS-based maps.

Image of GIS expedites learning, analysis, and decision-making by visualizing the desired geospatial information.
GIS expedites learning, analysis, and decision-making by visualizing the desired geospatial information.

Issues with conventional GIS, and the need for advanced 3D city models

Originally, the vast majority of GIS offered 2D displays, but with the advancement of technology, many systems now feature 3D displays capable of visualizing geospatial information more clearly for different purposes. Now, 3D display services are readily available, for example in smartphone map applications.

However, 3D displays in typical services are geometric models with 3D polygons comprising geometric representations (triangles or polygons) of the state of the ground surface—the displays do not distinguish between topographical features, buildings, adjacent buildings, streets, and other objects. Therefore, it is difficult to link positional information with 3D data and detailed geospatial information with meaningful precision.

For example, it takes an immense amount of time and money to create the precise, detailed 3D data to underpin advanced applications such as detailed analysis and simulation for city planning and disaster risk reduction planning, and to create digital twins of cities, which are essential for achieving smart cities. Amid these circumstances, the need for open, highly precise 3D city models has increased, prompting many countries to develop and utilize data.

CityGML, the international standard, and Plateau, Japan’s 3D city model

A common platform is essential for enabling national and local governments as well as corporations and individuals to utilize 3D data for a wide variety of purposes. In response, Japan adopted CityGML—the international standard established by the Open Geospatial Consortium (OGC), an international standardization organization in the field of geospatial information—making it possible to utilize the data from its 3D city models in a broad range of applications in Japan and around the world.

Additionally, CityGML deploys not only a conventional geometric model comprising uniform geometric shapes, but also a semantic model that classifies, defines, and assigns height and attribute information to each building and street. This makes CityGML compatible with advanced applications that require high precision and sophistication.

Plateau is a CityGML-compatible, open 3D city model created by the Japanese Ministry of Land, Infrastructure, Transport and Tourism with the aim of realizing the Society 5.0 concept. Although Plateau was launched later than other countries’ CityGML-compatible models, it is now the world’s most extensive open 3D city model, covering 56 cities, an area of 10,000 km², and 10 million buildings across Japan* with ongoing updates and expanded use cases.

* According to an August 2022 press release by the Japanese Ministry of Land, Infrastructure, Transport and Tourism

Plateau mainly comprises three types of data.

The first is data collected via the main means of creating conventional 2D data: aircraft. Specifically, this refers to height data from aerial surveying with laser profilers and image data from aerial photography. The second type of data is basic city planning maps: 2D map data provided by local and municipal governments. The third type is rich data: attributes, structures, specifications, classifications, ages, and other properties of individual buildings from legally mandated basic city planning surveys, which in the past were mainly used locally.

This excavation and repurposing of valid data from past surveys into a new format—3D city models—is believed to represent significant savings compared to the staggering cost of building the models from scratch.

Notably, Plateau offers downloadable open data compatible with a range of 3D graphics software in addition to Plateau View, an online application that allows users to view 3D models and associated data for any area or point (Figure 1).

Image of Plateau View provides a display of the buildings around Shibuya Station, color-coded by use.
Figure 1: Plateau View provides a display of the buildings around Shibuya Station, color-coded by use. (Displayed using Plateau View from the Japanese Ministry of Land, Infrastructure, Transport and Tourism,

Advantages of using open data from 3D city models

The open data of Japan’s CityGML-compatible 3D city model, Plateau, works with many applications and can also be used commercially, making it useful to national and local governments as well as companies and individual creators for a wide range of purposes in all industries.

Another major advantage is that Plateau provides 3D models linked to coordinates with a high degree of precision in addition to building textures and the corresponding attribute information, which is useful for many different purposes. The highly precise linkage to coordinates makes it possible to accurately assign the desired data to 3D models of the desired area or location. Thus, Plateau enables more advanced simulations and city planning, and can also be used to create digital twins that interlink cyberspace and the real world. It can also be used in entertainment and communication, for example to create precise 3D model-based backgrounds for video games or high-resolution virtual reality (VR) and augmented reality (AR).

Notably, CityGML facilitates centralized management of the detail of 3D objects based on the Level of Detail (LOD) concept. The system presently comprises up to four LOD, from LOD1, which renders buildings as cube-shaped objects, to LOD4, which illustrates building exteriors in intricate detail in addition to linking to 3D data of interiors (Figure 2). Changing the scale of conventional 3D objects is cumbersome, but CityGML makes it possible to centrally and efficiently manage, store, and utilize data for individual objects with multiple levels of detail. This enables seamless 3D displays of everything from bird’s-eye views of cities to close-up views of buildings and building interiors; the possibilities include creating digital twins of commercial facilities, allowing users to make real-world purchases from virtual stores in cyberspace.

Image of Overview of CityGML’s LOD concept
Figure 2: Overview of CityGML’s LOD concept (Prepared using data from the Plateau website published by the Japanese Ministry of Land, Infrastructure, Transport and Tourism,

CityGML also has a feature called Application Domain Extension (ADE) that extends the definitions of planimetric features and attributes, allowing the data to be added for different purposes (Figure 3). Additionally, data extended using the ADE format can be reused and repurposed.

Image of Data expanded using the CityGML ADE feature
Figure 3: Data expanded using the CityGML ADE feature (Prepared using data from the Plateau website published by the Japanese Ministry of Land, Infrastructure, Transport and Tourism,

Example applications of 3D city models

This section presents example applications of 3D city models in the CityGML format for different purposes, based on Plateau use cases.

Analysis and simulation for city planning

  • Detailed zoning can be studied using data from individual buildings, even where commercial and residential zones border each other. The ability to analyze building attribute information and other rich data to determine how conducive an area is to raising children, for example, is helpful in considering urban policy.
  • In cities situated such that they are susceptible to high temperatures during the summer, visualizing the movement and stagnation of hot air allows users to simulate, visualize, and consider how to make urban areas more comfortable for people to live in.
  • Visualize and analyze changes in cities from past to present. City planning precision can be improved by learning how the movement of people and vehicles changes when city sidewalks and roadways are changed.

Simulations for disaster risk assessment and disaster prevention planning

  • Using 3D city models that include height data to simulate and analyze disaster risk in a given area facilitates the consideration of highly precise, more sophisticated evacuation and disaster prevention plans.
  • Conducting simulations to visualize floods, tsunami, and other disasters makes it possible to project damage on a building-by building basis. For example, it is possible to plan for vertical evacuation—evacuation to tall buildings—which is effective for elderly people who cannot evacuate quickly and when people cannot access evacuation centers from their residences or workplaces. Cities are using effective data on building heights and attributes (e.g. whether they are made of reinforced steel or wood) for vertical evacuation to consider diversifying modes of evacuation, specifically by encouraging the inclusion of privately owned buildings in addition to public facilities.

Monitoring to improve urban areas and facilities

  • Visualizing and analyzing urban activities using data from cameras and sensors makes it possible to effectively simulate how people move around to improve sidewalks and other paths of movement in cities. Another method of research is initiatives where people wear smartwatches to visualize data on the paths they take—which cannot be fully understood using sensors or cameras—to identify and improve on issues in cities.
  • At major stations of high-speed railways and other large-scale facilities where people’s paths of movement tend to be complex, LOD4 can be linked to building interior data to visualize how people move around inside and outside stations and overlay simulations of the movement on 3D city models. Visualizing points where people tend to become lost or where congestion tends to occur can help improve flow lines and other aspects of spatial design.
  • Monitoring building attributes and how people move around a given point makes it possible to plan the best and most efficient placement of outdoor advertisements for the content of the pitch.

Utilization in communication and entertainment

  • CityGML-compatible 3D city models allow users to walk around cities or engage in customer service and communication in customers walk around cities and commercial facilities in 3D virtual spaces that link building interior and exterior data. Open data-based digital twins can be used to sell products and showcase cities at a reduced cost.
  • Sharing coordinate data enables both augmented reality (AR) users in real-world cities and virtual reality (VR) users in remote locations to sightsee, stroll around town, shop, and share other experiences in the exact same location. Additionally, using the attributes of data in which buildings are classified makes it possible to use AR to provide information and guide customers through stores in shopping districts. Efforts to attract tourists and revitalize communities are also being made by promoting cities to people in Japan and the rest of the world through games that incorporate real-world 3D data from the cities.

Data-driven efforts also enable efficient operation of electronic equipment

To this point, we have focused on example applications for digital transformations that affect cities and people. That said, electronic equipment is essential for monitoring cities to collect data, automating operations, and communicating the necessary data for these activities. Simulations and data from 3D city models can be used to study the efficient deployment of electronic equipment.

For example, we cannot install an unlimited number of sensors and cameras to monitor how people move around. Instead, we use 3D city data to conduct simulations to consider sensor and camera placement plans and use the results to streamline sensing and data collection with a limited number of units.

3D city model-based analysis and simulations can also be used to plan the placement of the base stations needed for wireless communications. 3D city models are also expected to be used in flight simulations for delivery drones, which are expected to become more widespread in the near future. If safe flight paths can be selected from 3D city models with height data for individual buildings, there will be no need to expend as much time on field surveys.

As demonstrated, CityGML-compatible 3D city models should be useful not only in policy development, planning, and services, but also in many other applications such as considering the required specifications and methods of operating hardware and devices. 3D city models are a major step toward popularizing and expanding the use of digital twins, and as use cases increase, the open data will grow richer and be more available for people in all industries and positions to apply their new ideas.

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