Understanding Digital Twin data

Digital Twins are 3D, dynamic digital representations of real-world objects, processes or systems. They’re used to interpret and visualise the real-world to better understand and virtually analyse the environment. In many cases, they can be used to predict future outcomes to help create change in the real-world.

In building a Digital Twin, lots of different datasets can be included to help turn the real-world into a virtual one - especially photogrammetry data. Images of the landscape and buildings, for example, can be used to create 3D data that is digitised into a Digital Twin and used for spatial analysis and visualisation.

Imagery and building information are just the starting point of a Digital Twin. Whether it’s an object (such as a cup, car or a building), physical process (such as manufacturing processes), or environmental ecosystem (like a precinct or a waterway), many other ‘foundational’ datasets can be included to build a virtual environment that gives decisionmakers deeper and richer insights into the world around them.

LiDAR

 LiDAR is a type of 3D scanning technology. It stands for Light Detection and Ranging and is used to create a detailed model of object it is scanning. This means LIDAR can be captured and processed to create 3D data for many types of features including the land surface (terrain), buildings, trees, road structures, water features such as water catchments, and even underground objects such as pipes. Modern LiDAR systems can achieve distance measurements within an accuracy of a few centimetres to several millimetres.

DEMs and DTMs

A Digital Elevation Model (DEM) is a pixelated map of the Earth’s surface. Each pixel holds a height value corresponding to the elevation at that location. This could be the height of a building or the surface elevation above sea level. This dataset acts as your ground surface in a digital twin, where buildings and other objects are oriented (georeferenced) and sit above or below this virtual ‘ground’.

Various types of DEM can be created, including a Digital Surface Model (DSM), which are useful for urban planning, power line corridor inspections or aviation as they include features of both the natural and built environment.

A Digital Terrain Model (DTM) typically represents the bare ground surface. In a DTM, vegetation and buildings are digitally removed, leaving just the underlying terrain. They’re mostly used for civil engineering, landscape design, geodesy, and surveying applications.

Reality Mesh

A reality mesh is a geospatially accurate 3D model of an area, where ground and above-ground features are reconstructed. They’re not unlike DEMs and DTMs. The difference is that they replicate the shape and structure of objects as a collection of faces (polygons), edges and vertices.

Meshes can be created through photogrammetry techniques which stitch an array of overlapping, high-resolution photos taken from different angles into a 3D mesh. These meshes can be explored and analysed from any perspective and are commonly used in computer-aided design and graphics, simulations, or virtual reality environments - offering a powerful tool for visualisation.

3D Building Models

Building models represent the built environment in Digital Twins. These are highly detailed digital renditions of a physical structure. Crafted with precision to mirror real-world buildings, they give a comprehensive view of the urban landscape.

A 3D building model is an external virtual replica of a building and interacts as an object within a digital twin. A 3D building model dataset can have data that is attributed each building, such as address, height measurement details, number of floors, and more.

Building models have different levels of detail, often categorised as Levels of Detail (LOD) that help explain the differences in building shape with a distinct level of intricacy and precision. They’re not to be confused with Building Information Models (BIM), which splits building detail into all its multiple asset-related parts and elements.

For local government, different levels of detail serve different purposes and impact precision of analysis. For instance, a LOD2.2 model enables analysis of building features (like chimneys, or other externally identifiable features). A lower detail does not. Increased LOD often enables further insights and analytical opportunities associated with structures and built form.

Textured Building Models

A ‘texture' is the skin of a building model providing visual context of the colour, texture or materials a structure is (or could be) made of. Textured Building Models provide a coloured, life-like representation of buildings within a Digital Twin.

Building Models vs. 3D Reality Mesh

While building models and 3D reality mesh may seem similar, they serve distinct purposes within a digital twin. Building models represent physical structures with geometric data, whereas 3D reality mesh uses aerial or satellite imagery to create a textured, three-dimensional model of the terrain. The main difference lies in detail and accuracy, with building models excelling in analysis and simulation, while 3D reality mesh offers a broader contextual visual understanding.

3D Building Models offer several benefits and analytical outcomes for local government. 3D building data, coupled with in depth modelling and analysis, can enable change for community outcomes in a range of different situations, including:

Evaluating proposed infrastructure changes:
Enables evaluation of proposed changes on individual structures and the urban environment.

Zoning regulation compliance:
Facilitates visualisation and scrutiny of zoning regulations to ensure alignment with city planning standards.

Emergency response planning:
Supports planning and response efforts by providing detailed information on the urban environment.

Infrastructure development:
Offers insights for infrastructure projects, including simulating new structures and optimising layouts.

Community engagement:
Enhances transparency and engagement by visualising proposed developments for residents.

The baseline, foundational dataset for a Digital Twin is LiDAR. Why? Because DEM, Reality Mesh and 3D Building models are all derived from LiDAR.

LiDAR is a data source that is procured. Local government, government and other organisations will seek the assistance of an aerial imagery operator to fly and capture data for the coverage area of importance. Once captured, the data is processed into usable geospatial data formats to become their different products that can be consumed by Digital Twins and other geospatial software.

LiDAR data is processed into Digital Twin data products core to creating a virtual representation and built environment analysis. To be able to be used effectively, the processing outputs need to be compatible with a Digital Twin and its geospatial software platform.

Local governments have access to a range of 3D data products that are either created independently, or commercially.

LIDAR: is often procured and captured by a local government as part of an internal geospatial imagery program. These raw files may be stored internally and can be processed into 3D data products.

DEM: Data can be processed by an imagery provider or independently depending on capability requirements. It can also be processed by LINZ through the National Elevation Program.

LINZ provides a base specification for DEM, DSM and Point Cloud procurement for these datasets to be added to the National DEM, DSM and Point Cloud data services. These datasets go into an open data service available to the public to download for free.

3D Building Models: Some local government agencies may have internal capability to help build this dataset from commercial or authoritative NZ products or thiscan be provided by imagery providers.

Depending on how the data is provided and curated, end data products may produce a different level of detail (LOD) influencing analysis.

While New Zealand doesn’t yet have a national 3D building model dataset that offers a high level of detail, including 3D building models in your Digital Twin can have transformative analytical and visual power.

Commercial Products: Google Maps, Apple Maps, NearMap, and others offer high-resolution imagery and AI-generated building models.

These products have different commercial offerings that may or may not be viable to use in a local government context. All have varying products, services, formats and imagery resolutions effecting accuracy and usability in a digital twin or geospatial platform.

Government Products: LINZ offer a building outlines dataset that provides a geometric outline of a building. This is a 2D representation of the roof outline of a building also known as LOD0. This dataset can be used as the pre-cursor to a 3D building dataset where the height is extruded to create a LOD1 3D building object.

These datasets can significantly enhance decision-making in urban development and are important in positioning these objects in the right place on our virtual surface, to be as aligned to the real-world as possible.

By integrating all these kinds of data into Digital Twins, local governments can gain valuable insights and achieve positive community outcomes for planning, infrastructure development, and community engagement. - ultimately helping shape efficient, sustainable, resilient, future-ready cities. 

Kerri and Istvan thank Professor Robert Amor from Auckland University's Computer Science Department for his peer review of this feature.