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Cesium for Omniverse v0.28.0

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User Stories

Purdue University’s Envision Center supports faculty across the university by creating 3D visualizations for research and classroom use. When researchers requested an immersive way of viewing complex spatial data, such as supernovas, heart models, and combustion engines, the Envision Center built CollabXR, a collaborative XR platform designed to ingest nearly any 3D dataset and explore it as a group. Now with the addition of Cesium for Unity, CollabXR supports geospatial data as well.

CollabXR, built by the Envision Center at Purdue University, allows people to explore complex 3D data in VR together as a group. Now with the addition of Cesium for Unity, they can also visualize geospatial datasets. Courtesy Purdue University. 

CollabXR Geospatial Visualization - Purdue Envision Center

Originally developed as a shared model viewer, CollabXR has grown into a multipurpose XR environment that supports visualizations ranging from astronomy and geoscience to cultural heritage and aviation safety. The platform runs on Meta Quest, Apple Vision Pro, and desktop systems, supporting both fully immersive VR and mixed reality.

Uluru in Australia, visualized with Cesium for Unity in CollabXR. The Purdue University Envision Center team has built an app that allows students to explore Earth using Google Photorealistic 3D Tiles. Courtesy Purdue University.

The CollabXR platform allows multiple users to engage with a single VR experience. Multi-user synchronization is handled through a networked architecture, while Unity performs client-side rendering and interaction, enabling participants to annotate, draw, and manipulate data together in real time.

“CollabXR has allowed us to bring in nearly any type of 3D model, but we’ve always wanted to be able to view geoscience data. With Cesium for Unity we’ve expanded the capabilities of CollabXR for earth and planetary sciences, cultural heritage, history, aviation, and other areas. Combining 3D Tiles with live feeds such as aviation ADS-B data, we are able to create holographic geospatial digital twins.” 

– George Takahashi, Principal Visualization Scientist, Envision Center, Purdue University

The Envision Center has brought a live ADS-B feed into CollabXR, allowing viewers to see live flights, like this visualization at the Chicago O’Hare Airport. Courtesy Purdue University.

Users of CollabXR can manipulate data in the environment. Here, a student pilot is landing a plane showing live tracked data from the university’s local Lafayette Regional Airport. Courtesy Purdue University.

On Purdue Aviation day, over 200 visitors engaged with live aviation data through CollabXR. Courtesy Purdue University.

Since integrating Cesium for Unity, the Envision Center has been able to add geospatial visualization to their repertoire. Cesium provides a high-accuracy WGS84 globe and streams real-world terrain and photogrammetry at runtime using open standards like 3D Tiles. This allows researchers to anchor domain-specific data, such as satellite orbits, atmospheric models, or live aviation feeds, directly to Earth and explore everything from city-scale sites to planet-scale environments within a single XR experience.

Google Photorealistic 3D Tiles of the Eiffel Tower in Paris, France, visualized with Cesium for Unity in CollabXR. The team built a demo visualization showing points of interest around the world. Viewers can interact with the geospatial data, highlighting key areas. Courtesy Purdue University.

Cesium’s streaming architecture makes it possible to visualize massive geospatial datasets on lightweight head-mounted devices without custom pipelines for each discipline. For students and developers, Cesium’s integration with Unity Game Objects and workflows has proven highly approachable: the majority of the artwork and code for each visualization produced by the Envision Center is done by undergraduate students, guided by a small core engineering staff.

Google Photorealistic 3D Tiles of London, England, visualized with Cesium for Unity in CollabXR. Faculty leading students on international experiences have used visualizations like this to preview trips for students before they go. Courtesy Purdue University.

The Envision Center is part of the Rosen Center for Advanced Computing, which operates the centrally maintained research computing resources at Purdue University. They’re dedicated to assisting, supporting, and collaborating with faculty, students, and industry in scientific visualization, virtual and augmented reality, and media creation. The center’s staff and student employees work with faculty partners and external clients to create VR and data visualization tools for research and educational use. The center also collaborates on grant proposals and develops promotional media, such as publication-quality stills and animated videos.

Google Photorealistic 3D Tiles of Mt Fuji, Japan, visualized with Cesium for Unity in CollabXR. Student observation of 3D geosciences, topography, and tectonic data enhances spatial exploration and communication. Courtesy Purdue University.

CollabXR is being prepared for open source release, with the goals of lowering the barrier for other universities and research groups to create shared XR environments and of expanding the reach of CollabXR use cases. By combining Unity’s XR ecosystem with Cesium’s high-accuracy geospatial platform, the Envision Center at Purdue University has created a flexible foundation for spatial computing to meet advanced research needs. To create your own real-world visualizations in XR, try out Cesium for Unity.

Purdue University Exploring the Boundaries of XR with Cesium

In complex, high-pressure environments, how information is presented can be as important as the information itself. XReality Factory (XRF) uses CesiumJS and Cesium for Unity for a single shared operational view for better, faster decisions across real operations and training scenarios, throughout defense, security, and emergency management.

XRF's tools consolidate data sources and connect agencies via a single shared operational view with 3D geospatial context for better decisions. Courtesy XRF.

XReality Factory

The volcanic eruptions on the Spanish island of La Palma in 2021 were the tipping point for XRF’s founding team, with expertise in extended reality and interactive technologies, to build tools to consolidate data sources and connect agencies via a single shared operational view with 3D geospatial context for better decisions.

“What we were developing in gaming is useful in emergencies, useful to our heroes,” said Raul Espada, XRF’s CRO.

XRF supports users in critical infrastructure, defense, emergency management, and security, working with the Spanish Armed Forces, Royal Netherlands Armed Forces, public authorities, and industry. In NATO exercises with armed forces from multiple nations on different systems, XRF tools served as the common operating picture (COP), enabling coordination across distributed teams, improving situational awareness, and accelerating decision-making with meaningful information, instead of a barrage of siloed data. The company is part of NATO’s EU Defence Innovation Scheme (EUDIS) and Defence Innovation Accelerator for the North Atlantic (DIANA) programs.

In NATO exercises, XRF tools served as the COP, enabling coordination across distributed teams. Courtesy XRF.

At the core of XRF’s dual-use command and control (C2) system is Compass, a platform for fusing data from several sources into a trusted 3D COP. With Cesium World Terrain or Cesium World Bathymetry via Cesium ion as Compass’s base, users add their own 3D models, drone imagery, and other information layers specific to their missions and organizational requirements for rapid, efficient delivery, streaming as 3D Tiles into CesiumJS for the web and Cesium for Unity for XR.

Around Compass, XRF developed complementary tools:

Apolo, a mobile app for units deployed on the ground, built with CesiumJS;

Colossus, a large multitouch command table for fixed control rooms, using CesiumJS;

Sandbox, an XR multiuser command center for planning, training, and operations, built on Cesium for Unity and device agnostic across Microsoft HoloLens, Meta Quest, and Apple Vision Pro; and

Hermes, XRF’s AI system that interprets scenarios to support decisions with natural language.

With real-world data available on a variety of devices, users can more quickly understand terrain, elevation, line of sight, and spatial relationships in context.

“Our goal has always been to integrate the solution the final user needs in their unifying system, so most of our effort goes into interoperability,” said Antonio Sanchez, XRF’s primary developer.

3D Tiles, an OGC community standard built on glTF and other 3D data types, enables XRF’s users to efficiently stream massive datasets, at any scale, together. The view their users need is the one that will load with the most detail, supporting immersive visualization and analysis on both high-end workstations and bandwidth-constrained devices.

XRF uses Cesium ion SaaS for testing, demos, and situations with reliable internet. The team and its users employ Cesium ion Self-Hosted for strict internal security requirements and off-grid environments.

“The level of performance—rendering continental-scale terrain down to tactical detail, with multiple users connected—is essential for user trust. In defense and emergency contexts, if the visualization stutters or lags, the system is not usable. The feedback we’ve received confirms that the 3D view is responsive and dependable,” Sanchez said.

XRF’s users report clearer briefings, faster alignment across teams, more confident decisions, and smoother transitions because of the connected, integrated approach, with the 3D geospatial foundation as a key enabler.

The volcanic eruptions on the Spanish island of La Palma in 2021 were the tipping point for XRF’s founding team. Pictured here is La Palma in XRF's Apolo, a mobile app for units deployed on the ground, built with CesiumJS. Courtesy XRF.

The volcanic eruptions on the Spanish island of La Palma in 2021 were the tipping point for XRF’s founding team. Pictured here is La Palma in XRF's Colossus, a large multitouch command table for fixed control rooms, using CesiumJS. Courtesy XRF.

XRF estimates that using Cesium reduced its time to first operational deployments by 30-40%. Because the team does not need to build or maintain the core 3D terrain or streaming architecture, they are able to focus on additional features—and lower their ongoing costs by replacing disconnected tools with one shared system, just as they’re doing for their users in defense, security, and emergency management.

Learn more about optimizing, hosting, and streaming your data in an immersive, shared source of truth for time-sensitive action.

Hear from XRF at the 2026 Cesium Developer Conference. Register to join us in Philadelphia in June.

XRF Connects and Integrates Missions with Cesium

As the Orion spacecraft journeyed around the moon during the historic Artemis II mission, space enthusiasts around the world have tracked its progress with Orbit Codex’s online flight tracker. Built on CesiumJS, the flight tracker offers an interactive 3D view of the spacecraft’s location and trajectory.

The Artemis II tracker in Orbit Codex shows the flight of the Orion spacecraft in CesiumJS using trajectory data from the JPL Horizons API.

Artemis II Tracker from Orbit Codex

Orbit Codex has tracked the real-time location of the Orion spacecraft from the moment of its launch using trajectory data from the JPL Horizons API. The interactive 3D capabilities in CesiumJS allow users to move forward and backward in time along the ship’s planned path, making it easy to understand orbital motion and mission phases.

Viewing the Artemis II mission in interactive 3D makes it possible to visualize the relative motion of Earth and the Moon together with Orion’s flight path.

With roots in the aerospace industry, Cesium was designed from its inception for the high precision, time dynamic demands of space visualizations. A highly accurate WGS84 ellipsoid model of Earth and skybox with correct star and Sun positions, combined with its ability to efficiently render solar system–scale data directly in the browser makes CesiumJS the engine of choice for numerous space applications.

“Orbit Codex is a massive database of over 14,000 entities across the entire solar system, including rocket launches, over 8,000 satellites, and extensive space debris. I needed a WebGL engine capable of rendering a massive swarm of live objects smoothly. Cesium is the absolute gold standard for handling that level of scale.” 

The Artemis II tracker is only one small piece of Orbit Codex. As space exploration has expanded across governments and commercial sectors, information about launches, spacecraft, and missions has become wider spread. Frustrated by the fragmented nature of space data, founder Bret van Putten harnessed his professional expertise as an AI consultant and startup founder to build a comprehensive real-time space operations platform. 

Orbit Codex brings together data from dozens of sources into one unified, interactive platform that tracks launches, spacecraft, astronauts, and missions across the solar system. Data drawn from The Space Devs API is enhanced with hand curated data and a custom Google Vertex AI pipeline that uses search grounding to autonomously collect and structure historical data from verified sources.

In addition to tracking the Artemis II mission, Orbit Codex uses CesiumJS to visualize numerous other activities in space. Here moon rovers are shown on Cesium Moon data. Courtesy Orbit Codex.

Across Orbit Codex, CesiumJS acts as both a visualization engine to illustrate concepts and as a spatial index for accessing the site’s datasets. Users can dive into a detailed dossier on any entity and then instantly launch into a real-time 3D environment showing a base’s launch pads, a satellite’s current orbit, or a planet’s surface.

Visitors to Orbit Codex transition seamlessly between detailed information about numerous space topics and 3D visualizations in CesiumJS, like this view of the launch pads at Cape Canaveral, Florida.

Orbit Codex’s extensive encyclopedia covers 18 categories, from moonbases to rovers. Visitors can explore detailed views of more than 350 launch and landing sites in CesiumJS, read about propulsion systems, view a catalog of the more than 350 organizations working in space, and read the profiles of more than 800 astronauts. They can also track over 20,000 Earth-orbiting satellites and debris in a CesiumJS visualization that pulls TLE data from the CelesTrak and Space-Track catalogs. Space debris entries are enhanced by ESA DISCOS data describing physical properties such as mass and dimensions. Visitors will also find models of all eight planets in the solar system; Orbit Codex uses Cesium Mars and Cesium Moon for off-Earth terrain and imagery. 

Orbit Codex is a comprehensive repository of information about space, bringing together historical and current data from public and private enterprises, as with this entry on the Athena lunar lander.

As this Artemis mission draws to a close, Orbit Codex’s journey is just beginning. The site is growing to become a “space time machine” that allows users to scrub back to 1969 to watch a replay of Apollo 11, to follow active missions from launch to touchdown, or to look ahead to future space infrastructure, such as moon bases, habitats, and space elevators.

Orbit Codex points both forward and backward in time, creating an archive of past missions to space and looking ahead to humanity’s future forays into the universe.

CesiumJS provides the aerospace-grade precision and planetary scale for these ambitious plans. Sign up for your own Cesium ion account to begin developing with Cesium.

Orbit Codex Tracks Flight of Artemis II in CesiumJS

The Netherlands, perhaps more than any other country, appreciates how critical what lies below the surface is to what's built above. Much of the country sits below sea level, meaning groundwater is high, and centuries of silt and sand deposits from continental rivers mean the soil is soft. Consequently, understanding the makeup of the ground is of paramount importance for city planning.

Bedrock.engineer visualizes large geospatial subsurface datasets using 3D Tiles voxels. Here they use 3D Tiles voxels to visualize GeoTOP, a public geological model of the Netherlands by the Dutch Geological Survey. Courtesy Bedrock.engineer.

Visualizing national scale subsurface data with 3D Tiles voxels

GeoTOP demo by Bedrock.engineer

Unfortunately, subsurface data is challenging to share: the science is highly technical, and visualizations are often limited to PDFs, hand‑drawn cross sections, or specialized desktop software. That’s why Bedrock.engineer was founded. Bedrock.engineer works to make geotechnical data—boreholes, CPT tests, ground models, and analysis results—more accessible and easier to integrate into the tools engineers and stakeholders use. One of their interests is 3D visualization of subsurface models in the browser. Using the 3D Tiles 2.0 draft voxels extension in CesiumJS, they are streaming large subsurface datasets, demonstrating how open-format 3D Tiles enables geological voxel models to be explored in spatial context directly in the browser. Open source software and open data formats are central to how Bedrock.engineer works.

Bedrock.engineer visualizes subsurface data, like these boreholes in Hong Kong, together with above ground data in CesiumJS. Courtesy Bedrock.engineer.

Subsurface visualization with 3D Tiles voxels

Voxel representations, which can model continuous volumes and store material properties such as soil type, are ideal for subsurface datasets that hold continuous data like sediment layers. But visualizing very large voxel datasets in a geospatial context was not possible with open standards before 3D Tiles support.

Bedrock.engineer visualizes GeoTOP’s 50m deep subsurface data covering the entire Netherlands in CesiumJS using voxels. Courtesy Bedrock.engineer.

With the addition of voxel support in the draft 3D Tiles 2.0 specification, Bedrock.engineer can now combine voxel‑based subsurface models with 3D Tiles’ hierarchical streaming. Voxel renderings are currently a 3D Tiles extension and are part of the 3D Tiles 2.0 proposal, which was described at the 134th OGC Member Meeting in March. Bedrock.engineer has built their own Python tooling to convert gridded scientific formats, such as NetCDF, into 3D Tiles. 3D Tiles makes it possible to visualize dense, volumetric datasets covering an entire nation directly in the browser.

Bedrock.engineer brings GeoTOP data into CesiumJS using the 3D Tiles open standard, as in this dataset from Amsterdam. Courtesy Bedrock.engineer.

3D Tiles voxels make visualizing geoscience models possible, and bringing those 3D Tiles into CesiumJS makes it usable. What Bedrock.engineer appreciates most about CesiumJS is that visualizations are widely accessible to anyone with the link, allowing technical and nontechnical stakeholders to interact with the data directly.

"What 3D Tiles voxels change is accessibility. Subsurface models that used to require specialist desktop software can now be explored directly in the browser, in true 3D, in spatial context with the world above ground. And because it’s an open format, there’s no lock-in: anyone can build on it and combine it with their own data. That considerably lowers the barrier." 

– Jules Blom, Cofounder Bedrock.engineer

By bringing subsurface data into CesiumJS, Bedrock.engineer is also able to combine that data with other datasets, including terrain and buildings, for a more complete picture. For city planning, seeing what is below ground is only valuable if it’s shown in context with the natural and built environment above. Building on CesiumJS, Bedrock.engineer has implemented multivariable filtering, allowing users to see just the relevant data for any given application.

Fence diagrams make it easier to see layers of subsurface sediment. Courtesy Bedrock.engineer.

A prime example of Bedrock.engineer’s work is their CesiumJS visualization of GeoTOP, a public geological model of the Netherlands by the Dutch Geological Survey. By bringing GeoTOP into CesiumJS as 3D Tiles, Bedrock.engineer can embed the model in any browser-based application, combine it with other datasets in spatial context, and build custom tools on top of it, all using an open standard.

Every square meter of land in the Netherlands is designated for a particular use, such as agricultural, urban development, or green space. Municipalities are legally obliged to consider subsurface data whenever it is relevant to a public task. Courtesy Bedrock.engineer.

The GeoTOP model is well suited for governments seeking to better understand the geological features of their area at a regional scale. In the Netherlands, government bodies are legally required to consult BRO subsurface data, including models like GeoTOP, whenever it is relevant to a public task. Bedrock.engineer’s visualization makes it easier to understand and communicate what that data actually shows. When a local government can clearly see what’s below ground, they can make better decisions around spatial planning, groundwater management, land subsidence, and dike safety assessments.

Such visualization can also be useful to building developers in the early stages of a project. Knowing whether they’ll be dealing with peat or sand makes a significant difference when considering foundation type. Though GeoTOP is not a substitute for a full geotechnical investigation, but it gives a useful first indication before that work begins.

Semi-transparent voxel rendering of geophysical models reveals subsurface structures, creating an X-ray–like view of the underground. Data courtesy Emerald Geomodelling, image courtesy Bedrock.engineer.

Bedrock.engineer is working to add GeoTOP data to the LEIA viewer, a CesiumJS-based digital twin for the provincial government of Zeeland, Netherlands. Bringing GeoTOP into LEIA will allow policy makers to see subsurface data in spatial context with other government datasets. Bedrock.engineer has also brought a shallow subsurface model of the Antwerp urban region and harbor into CesiumJS, visualized as 3D Tiles voxels.

Voxel support is part of the draft 3D Tiles 2.0 specification, a key aspect of our commitment to open standards. If you’re working with volumetric data, explore the 3D Tiles OGC Community Standard, try it in CesiumJS, and share your feedback on GitHub. We’d love to see your implementation.

Bedrock.engineer Streams Subsurface Data at Nation Scale with 3D Tiles Voxels

Matom.AI is applying AI to city‑scale point clouds, extracting meaningful insights from complex geospatial data for city management, power line inspections, and forest analysis. A Cesium Certified Developer, Matom.AI uses CesiumJS to build digital twins from massive datasets, including custom terrain, CityJSON, photogrammetry, orthophotos, and point clouds. The real innovation of Matom.AI’s platform is their AI‑driven approach to analyzing this data.

Matom.AI uses AI tools to segment point clouds and identify common elements such as trees and lamp posts. Here, they’ve automatically classified and modeled urban assets in a digital twin of Kaunas, Lithuania. Courtesy Matom.AI. 

Because CesiumJS and 3D Tiles make massive geospatial datasets easy to stream and visualize, Matom.AI can apply AI directly to raw city data, eliminating the need for labor-intensive modeling and enabling scalable, continuous analysis.

While a traditional digital twin requires developers to manually clean data, hand-build models, simplify, and then visualize, Matom.AI has flipped this order. They bring point clouds directly into CesiumJS and visualize first, then analyze at scale and structure with AI. These digital twins make it possible for teams in different locations to work with complex geospatial data directly in the browser, where they visualize large‑scale 3D datasets in a unified, high‑performance environment.

By fusing datasets captured at different times and from different perspectives, Matom.AI’s digital twins provide a more complete view. Cesium enables these diverse data sources to be visualized seamlessly within a single platform. Streamed in the browser as 3D Tiles, the data supports shared workflows, custom analysis, and reporting. The platform also supports real-time data collection through a mobile app, allowing field teams to capture information and add updates directly to the digital twin.

“CesiumJS allows us to deliver a truly collaborative digital twin that all stakeholders can access simultaneously. Everything streams directly in the browser, so teams across a city can make decisions together in real time.”

– Julius Gelšvartas, Chief R&D Officer and Co-Founder at Matom.AI

Matom.AI’s platform integrates AI-driven point cloud classification and instance segmentation, automatically detecting benches, poles, traffic signs, trash cans, and other urban assets. Each object can be analyzed individually and converted into structured models, making visualization and inspection more efficient. Built-in tools also calculate core characteristics of each element, such as location, height, and width, simplifying inventory management and infrastructure assessments.

AI-powered image segmentation, combined with measurement analysis tools, provide quick insight into large datasets, as in this detail view of a bus stop in Kaunas, Lithuania. Courtesy Matom.AI.

One of the most valuable capabilities Matom.AI provides is AI-powered change detection. By comparing scans captured at different points in time, the system highlights changes in buildings, vegetation, and city assets, helping users identify issues earlier and prioritize maintenance before small problems grow into larger challenges.

Here, Matom.AI highlights discrepancies between two datasets: one captured in winter and the other in summer in Kaunas, Lithuania. Courtesy Matom.AI. 

By making point clouds easier to analyze and act on, Matom.AI enables cities to collect data more frequently and maintain a continuously up‑to‑date digital twin. To visualize and analyze your point clouds in a geospatial environment and easily share with colleagues, bring them into CesiumJS using 3D Tiles.

If you are building creative solutions with Cesium, consider applying for the Cesium Certified Developer program, an opportunity to demonstrate your expertise and connect with other developers in the community.

Matom.AI Extracting AI Insights from Point Clouds in CesiumJS

Last month Camptocamp released Geo Challenge, a browser-based game built on CesiumJS that challenges users to identify randomly selected locations in Switzerland, France, or Germany.

Geo Challenge awards players points based on how close their guesses are to a 3D view’s actual location. Courtesy Camptocamp.

The game uses high precision datasets—swisstopo’s high‑resolution topographic data for Switzerland and Google Photorealistic 3D Tiles served by Cesium ion for France and Germany. The game is purely for fun, but the simple interface belies the sophistication of the massive datasets, 3D tiling pipelines, and geospatial rendering that make it possible. By using CesiumJS, Camptocamp transforms complex 3D data engineering into a playful, interactive experience that invites users to feel the value of high-precision geospatial data.

GeoChallenge by Camp to Camp

“With Cesium we’re able to give players a view of their countries with such accurate terrain that many are able to recognize the spot instantly. Players aren’t just guessing coordinates; they’re exploring.” 

- Frédéric Junod, Camptocamp developer and the game’s creator

In Switzerland, Geo Challenge uses swisstopo’s high-resolution datasets, rendering every peak and valley of the country. Courtesy Camptocamp.

Camptocamp shares Cesium’s commitment to open, collaborative technology and has extensive experience building with CesiumJS. A decade ago they worked with Switzerland’s Federal Office of Topography, swisstopo, to build an interactive 3D map of the entire country using CesiumJS. They were also an early adopter of Cesium’s subsurface rendering capabilities, used to show geological features below ground. Camptocamp is a Cesium Certified Developer organization, and they continue to provide geospatial services for companies and governments in Europe.

The Swiss players in particular are intensely competitive (and very good!), with many players having near perfect scores. Courtesy Camptocamp.

To see what experiences you can create with 3D geospatial data, try out CesiumJS.

Cesium Powers Camptocamp’s Geo Challenge Game

The E1 Series is the world’s first all‑electric race boat championship, bringing together cutting‑edge engineering, global competition, and high-profile star power. With celebrity‑owned teams and events spanning iconic waterfronts from Jeddah to Monaco, the sport pairs high performance with high glamour. Its RaceBirds—ultralight carbon craft powered by a 150 kW electric motor and lifted by hydrofoils—slice across the water at speeds of up to 50 knots, showcasing the future of sustainable racing and raising awareness for marine conservation.

For such an innovative sport, it should be no surprise that E1 provides a premium digital fan experience, created by BADASS Studios using Cesium for Unreal.

BADASS uses Cesium for Unreal to build a digital replica of E1 race venues, which is used in live broadcasts. Courtesy BADASS Studios.

BADASS builds a precise digital replica of every E1 race venue in Unreal Engine to provide an accurate, large‑scale replica of the environment with event-specific markers, sponsorship markers, and more for enhanced fan experience. Courtesy BADASS.

BADASS Studios: Digital Fan Experience for E1

Building the scene with Cesium for Unreal

For each race, BADASS builds a precise digital replica of the venue in Unreal Engine, using Cesium for Unreal to bring in Google Photorealistic 3D Tiles, which provide an accurate, large‑scale replica of the environment. BADASS artists then add event-specific elements: waypoint markers, shoreline grandstands, and custom buildings along the route, as well as lighting and color adjustments for a vibrant look. They also place sponsorship overlays: a win-win that provides high visibility for sponsors without polluting the oceans and views with billboards or other debris.

Still image of an E1 Series broadcast in Monaco. Courtesy BADASS Studios.

“BADASS operate at the intersection of creativity and technology. Their team take complex data, live telemetry and, working within the constraints of live broadcast, turn them into compelling XR experiences. They are agile, solutions-focused and deeply collaborative and have quickly become an essential extension of E1's content and product function.”

- Laurence Boyd, Chief Content and Product Officer, E1

The digital replica in Unreal provides a critical resource for live broadcasts of the race. During events, BADASS receives updates from a live telemetry feed that captures boat position, lift, trim, throttle, RPMs, and more. Their platform sanitizes the data and maps it onto the digital replica so every animation, AR label, and camera angle is synchronized with what’s happening on the water. Cesium’s geospatial accuracy means AR overlays don’t rely on tracking the broadcast feed. When the environment is removed and replaced with live video, the overlays stay perfectly aligned, enabling broadcast‑quality XR even in chaotic conditions where drone restrictions, line of sight challenges, or hardware issues can disrupt traditional filming.

With all the resources available in the Unreal environment, broadcasters can provide viewers with a visually interesting and deeply informative video by cutting back and forth between a live camera feed of the race, the digital replica in Cesium for Unreal, and a hybrid AR view of the race with data on the RaceBirds’ telemetry.

BADASS provides AR overlays for broadcasts of races, like this race in Monaco. Courtesy BADASS. 

The Cesium replica of the race isn’t just for broadcasts. Fans who come to watch the E1 Series can also take part in the races themselves in a game simulator. Players pick a team and a RaceBird and try their hand at piloting through the course, using the same environment BADASS built in Cesium for Unreal to use in course explainers and live broadcasts of the race. For onsite attendees, these simulators fill downtime between races and deepen engagement. In the future, these environments will also be published as a game on Steam and other platforms, allowing fans to play at home.

“Cesium’s streaming and geospatial accuracy give us a single environment we can reuse across course explainers, AR broadcast graphics, and interactive experiences, which makes delivery faster and the output more consistent.”

BADASS Studios reuses the same Cesium for Unreal race venue for VR and AR broadcasts and for simulations. They bring their adaptable approach to multiple live events, as shown in this simulation of the FIA Extreme H World Cup in Qiddiya City, Saudi Arabia. Courtesy BADASS Studios. 

This multi-use approach—creating a single environment that can be reused in marketing, broadcasting, and games—is only possible because of Cesium’s geospatial accuracy and streaming efficiency. Such reusable content deployed in so many ways simplifies the process for E1, which can solve many needs with a single digital twin, and for BADASS, which maximizes the use of the assets it builds.

In addition to the E1 Series, BADASS Studios supports a number of events, including the FIA Extreme H World Cup, an off-road race of hydrogen powered SUVs, and FIM World Supercross Championship. With a scalable platform built on Cesium, they plan to expand into other sports and entertainment live events, giving viewers in any location an enhanced connection to real events.

To build a geospatially accurate environment you can deploy in numerous ways, try out Cesium for Unreal.

Creating an XR Connection to the E1 Series with Cesium for Unreal

Matteo Massimi is an avid mountaineer. So when he took his most recent trip to Central Asia, there was nothing unusual about the hikes. What was new was his ability to plan the expedition in the app he created with Cesium: Trailamo.

Trailamo uses CesiumJS to bring open geospatial data to mountaineers so they can plan safer, more informed routes anywhere in the world with advanced 3D terrain analysis and layered datasets.

Trailamo demo

Trailamo is built on CesiumJS and tailored to the way an explorer like Matteo, looking for off-the-map adventures, plans outdoor experiences. With a highly precise WGS84 ellipsoid and the ability to render high-quality geospatial datasets, CesiumJS gives Trailamo a solid foundation for its sophisticated terrain analysis and numerous planning tools. 

Explorers can create their own routes in Trailamo, dropping waypoints and comparing against public routes, as in this climb of the southwest face of the Matterhorn. Courtesy Trailamo.

“I’m not a software developer by training, but I knew what features I needed in the ultimate mountaineering app. So I looked for what tools were available to a noob like me, and with Cesium I could build exactly what I needed.”  

Trailamo offers global terrain and imagery for planning an outing anywhere on the planet. Beginning with Cesium World Terrain, users can then choose from a variety of imagery layers, such as topographic maps or satellite imagery. For a photorealistic view of well-known areas, they can also view global Google Photorealistic 3D Tiles.

Trailamo aggregates open data, using CesiumJS to give viewers access to public datasets for planning outdoor experiences, as in this view of Mont Blanc in the Alps from the French approach. Courtesy Trailamo.

Above this base, users can add overlays, such as live snow coverage from NASA GIBS, weather data from OpenWeather, ski pistes from OpenSkiMap, hiking trails provided by various collections of public GPX tracks, and more.

By combining terrain, imagery, and overlays, users can better understand upcoming adventures. Here hiking trails, publicly available routes, ski runs, and terrain contours are all shown with OpenTopoMap imagery draped over Cesium World Terrain at Fizkul Peak in Kazakhstan. Courtesy Trailamo.

Trailamo offers free accounts. Matteo, a strong supporter of open data, believes that high‑quality outdoor tools shouldn’t hide essential information behind steep subscription fees—especially when much of that data is generated by publicly funded government agencies as a public good. If citizens have already paid to collect it, he argues, they shouldn’t have to pay again to access it.

Terrain analysis tools, such as this calculation of avalanche angles at Aconcagua, Argentina, give adventurers a better understanding of their surroundings so they can mitigate their risk in unknown territory. Courtesy Trailamo.

Matteo has also written a number of tools for specialized terrain analysis. Because CesiumJS exposes the quantized mesh in its terrain pipeline, Matteo was able to calculate normal vectors for each triangulated surface and use that calculation to display altitude and slope gradient, avalanche angles, and terrain aspect and contours. 

Combining layers and overlays with tools can help users answer very specific questions about planned trips. In this screenshot of the Trans-Ili Alatau range in Kazakhstan, only peaks above a certain altitude are visible, and the slope gradient is colored to give a better understanding of the steepness of the terrain. Courtesy Trailamo.

Because Trailamo uses Cesium to aggregate numerous public datasets into a single app, users can combine them for better insights. This means that skiers can look at runs in their area overlayed with NASA‑collected snow coverage and check for avalanche angles in the backcountry for areas of risk. Hikers venturing into remote areas without widely published guidebooks and trails can look at the 3D terrain and overlay that with GPS tracks collected by OpenStreetMap to infer where others have traveled—quite literally following in past footsteps.

“Aggregating this open data with Cesium gives me the tools to have free outdoor experiences that would have been much more challenging, if not impossible, ten years ago. I’ve climbed new mountains because of Trailamo.” 

Matteo’s future plan is to continue to expand Trailamo’s data offerings, bringing in more open source data and allowing users to add their own open source imagery or overlays. 

To bring together the datasets you care about, sign up for a free Cesium ion account.

Planning Mountaineering Routes in CesiumJS with Trailamo

Over the last 20 years, technology and the nature of conflict have changed more rapidly than US defense policies and military procedures. To modernize and synchronize operational-level planning, Sandtable uses CesiumJS, Cesium for Unity, and Cesium ion to combine traditional military planning documents and immersive geospatial context.

For operational wargaming in the COA analysis step of the MDMP, as well as mission rehearsal, Sandtable Navigator provides a 4D environment built with Cesium for Unity. Pictured here are friendly and enemy units at the National Training Center at Fort Irwin, California, USA. Courtesy Sandtable.

For operational wargaming in the COA analysis step of the MDMP, as well as mission rehearsal, Sandtable Navigator provides a 4D environment built with Cesium for Unity. Pictured here are friendly and enemy units at the National Training Center at Fort Irwin, California. Courtesy Sandtable.

Sandtable: COA Analysis

Founded in 2024 by US Army veterans and researchers, Sandtable pairs AI with human judgment in its Mentat and Navigator prototypes to facilitate mission analysis, course-of-action (COA) development, and operational wargaming with more data, detail, and speed.

Planning, collaboration, and rehearsal tools tend to involve 2D imagery, spreadsheets, printed documents, a physical sand table, and the risks that come with putting a group of key people in the same place simultaneously. The company’s push to bring time-dynamic 3D to military planning results in interactive environments that fuse data types and sources to support planning and assessment for both human teams and autonomous systems, no matter where they are. 

During COA DEV, planners using Sandtable Mentat create, visualize, and share unit symbology, operational graphics, viewshed, and ranges of weapon systems in 4D. Courtesy Sandtable. 

“What we’re simulating and planning—like drones, counterdrone technology, and electromagnetic warfare—exists in 3D space in reality, and we need to be able to represent reality. That requires Cesium,” said Sandtable COO Brady Moore. 

And reality is complex: data comes from myriad sources, and conditions shift over time. With AI, the platform helps surface patterns, compare options, and stress-test assumptions, so commanders can focus their judgment where it matters most.

Planners drag and drop MIL STD 2525D symbols from predefined combat power data to build enemy SITEMPs and friendly COAs in Mentat. Courtesy Sandtable.

Planners drag and drop MIL STD 2525D symbols from predefined combat power data to build enemy SITEMPs and friendly courses of action in Mentat. Courtesy Sandtable.

Sandtable: Enemy SITEMPs and Friends COAs

Cesium is deployed across Sandtable’s solution to accelerate key phases of the military decision-making process (MDMP), particularly mission analysis, COA development, and rehearsal, with authoritative geospatial context and efficient data delivery:

Mentat, built with CesiumJS, incorporates written orders, concept sketches, and open datasets, e.g., for soil density and composition, on top of real-world terrain in a browser for rapidly adjusting COAs with AI.

Navigator uses Cesium for Unity for COA analysis and mission rehearsal in a shared virtual environment, wherever participants are, on a variety of devices. Instead of merely rehearsing plans produced in Mentat, Navigator feeds insights back into the planning environment—enabling continuous refinement rather than one-time execution.

Sandtable Mentat allows planners to determine which factors about the terrain are relevant to operations and visualize them together or separately. Courtesy Sandtable. 

With detailed geospatial data from Cesium ion and a range of public and government sources (for example, NOAA and USDA datasets), warfighters and autonomous vehicles know not only where hills and trees are but also microterrain features relevant to mobility and line of sight. This is important because factors like height of vegetation determine what a drone can—or can’t—see (depending on available data resolution and source quality). This data is primarily 3D Tiles, quantized mesh, and KML/KMZ, optimized, hosted, and streamed via Cesium ion for efficiency and interoperability. Cesium ion also enables Sandtable to be data agnostic, because 3D Tiles is an OGC community standard, and can use the Army's own Well Formed Format data when available. Sandtable uses Cesium ion SaaS while connected to the internet and anticipates leveraging Cesium ion Self-Hosted in future disconnected or denied environments, as well as secure enclaves.

Sandtable Mentat develops its own Modified Combined Obstacle Overlay (MCOO) using CesiumJS to visualize layers. Sandtable’s detailed datasets help determine terrain trafficability. Other terrain data includes canopy height, land use, soil attributes, slope, and elevation. Courtesy Sandtable.

Sandtable Mentat develops its own Modified Combined Obstacle Overlay (MCOO) using CesiumJS to visualize layers. Sandtable’s detailed datasets help determine terrain trafficability. Other terrain data include canopy height, land use, soil attributes, slope, and elevation. Courtesy Sandtable.

Sandtable: Modified Combined Obstacle Overlay (MCOO)

Critical to Sandtable’s work is embedding with the very people who will use the platform. During the Army’s xTechOverwatch competition in October 2025, the team tested Mentat on a tablet in the field with soldiers during the day and adjusted the capabilities and interface each night, returning the next day with an improved product. Sandtable developers were able to take feedback from concept to functional visualization and analysis in hours rather than days. This speed of development is enabled by adaptable, streaming-ready 3D Tiles and open-source runtimes. (The company’s CEO, Brian Hamilton, is a Cesium Certified Developer, and Sandtable was among the competition’s winners.)  

Watch Sandtable CTO Brent Lance’s 2025 Cesium Developer Conference talk to learn about the role Cesium plays across Sandtable’s solution for the MDMP. 

Military Planning Using Agentic AI and Simulations

Mentat and Navigator have been deemed Awardable on the Tradewinds Solutions Marketplace, making them eligible for government procurement and tightening collaboration between government and industry.

Use Cesium ion to securely fuse high-resolution imagery and terrain with unit-specific data for actionable information and collaboration. Get started with a community account.  

Author’s note: Sandtable’s COO, Brady Moore, is a former Cesium employee. 

Sandtable Modernizes and Synchronizes Military Planning with Cesium

Blenheim Palace, a UNESCO World Heritage Site and one of England’s most iconic estates, faces a monumental challenge: maintaining a 300-year-old building that welcomes over one million visitors annually, while also serving as a lived-in residence.

Blenheim Palace, a UNESCO World Heritage Site and one of England’s most iconic estates. Courtesy Blenheim Palace.

To keep up with these challenges, Blenheim Palace has invested in an IoT sensor network that monitors all sorts of data from the building, such as temperature, humidity, CO2 levels, and footfall.

The data, pouring in from over 30 platforms, became too much for their building management system (BMS) to take in and ended up siloed, often buried in folders. Maintenance teams, facing restoration costs of £4 million a year and overwhelmed by the sheer volume of data, found it nearly impossible to get a comprehensive picture of the state of the palace, let alone plan for the future.

At 300 years old, Blenheim Palace requires constant maintenance and reconstruction work. Courtesy Blenheim Palace.

That’s all changed now that they’ve developed a digital twin of Blenheim Palace, built with Cesium, that provides a single source of truth for the state of the palace. IoT sensors feed real-time alerts into a unified platform, allowing maintenance teams to visualize issues in context, plan restoration work proactively, and even receive automated notifications when environmental thresholds are breached.

Blenheim digital twin for smart conservation

Blenheim Palace’s digital twin was born with the announcement of the Cesium Design Tiler and Add-In for Autodesk Revit. The team at Blenheim saw that the 3D Tiles open standard would allow them to efficiently stream heavy Revit files into a lightweight environment, providing a frontend through which they could access all of the IoT data they were collecting.

Loaded in CesiumJS, the interactive palace model streams smoothly despite its size and complexity thanks to 3D tiling via the Cesium ion for Autodesk Revit Add-In.  Courtesy Blenheim Palace.

In partnership with the Heritage Innovation Laboratory Oxford and Oxford Brookes University, Blenheim’s team worked to make their BIM model the foundation of a digital twin. They sliced their architectural model into over 14,000 individual elements, each tied to metadata: material type, historical repairs, risk assessments, etc. Then, using the Revit add-in and the Design Tiler in Cesium ion, they tiled the model into 3D Tiles. Now with a model that retained all the detail and metadata of the original but tiled for smooth navigation, they loaded the 3D Tileset into CesiumJS.

The original palace model came from a scanned point cloud, corrected by architects and tied to floor plans. Courtesy Blenheim Palace.

With the Revit model as the frontend, the palace’s intricate structure became an interactive digital twin. The model of the palace is easy to navigate, accessible to both technical and non-technical staff. Users can filter views of the site, for example, by restoration needs deemed most urgent in a recent risk assessment.

Users can filter views of the site, for example, by restoration needs deemed most urgent in a recent risk assessment. Courtesy Blenheim Palace.

Behind the interactive model sits Blenheim’s entire IoT network. By centralizing data with Cesium and automating alerts, Blenheim Palace reduced manual oversight and enabled proactive maintenance, potentially lowering restoration costs by up to 10%.

Blenheim Palace’s digital twin has a growing database currently exceeding 150 million rows of environmental and building data, fed by IoT sensors integrated with BMS controllers. Courtesy Blenheim Palace.

Predictive maintenance guided by AI insights

The digital twin also contains archival data tied to the model. This historic view, developed by Clara Saliba, makes the model a portal to the archives, giving users access to decades of maintenance history and to machine learning models trained to identify patterns in stonefall, water ingress, and exfoliation. These machine learning models are expected to enable predictive maintenance and sustainable energy use.

“Heritage isn’t just about preserving the past—it’s about imagining its future. With Cesium ion, we turned our Revit model from a virtual replica into a digital twin of Blenheim Palace—a dynamic simulation that tracks condition and restoration data, identifies inefficiencies, predicts future needs, and transforms how we manage heritage through technology.” 

- David Green, Head of Innovation, Blenheim Palace