Cesium for Omniverse v0.29.0

Cesium for Unity Samples v1.25.0

CesiumJS 1.144

User Stories

インフラ分野では、現実の施設や現場を3Dデータとして取得し、管理する取り組みが急速に広がっている。 CalTaのTRANCITY ARCADEは、Cesium ion、3D Tiles、Cesium for Unrealを基盤として、教育や訓練、安全理解、施設案内、コミュニケーションのための体験型アプリケーションを実現している。 

工事現場の３Dモデルをゲーミフィケーションコンテンツに使用　(提供：CalTa株式会社) 

点群、写真測量、3Dモデル、Gaussian Splattingなどの技術により、鉄道、発電所、都市空間、公共施設といった複雑な環境を、これまで以上に高精度にデジタル空間へ再現できるようになってきた。 

こうしたデータは、施設の構造を把握し、設備同士の関係を理解し、安全上の注意点を学ぶために活用されている。また、若手技術者に対して、普段は簡単に立ち入ることのできない施設の全体像を伝えたり、地域やステークホルダーにインフラの役割や価値を分かりやすく共有したりすることにも役立っている。 

CalTaとキャドセンターが共同で開発するTRANCITY ARCADEは、、この問いに対する一つの答えである。インフラの3Dデータを、教育、訓練、安全理解、施設案内、コミュニケーションのためのインタラクティブなアプリケーションへ展開し、人々が学び、理解し、共有し、現場での判断に活かせる環境を実現している。 

TRANCITY ARCADEは、写真、点群、3D Gaussian Splattingなどの現実世界のデータから生成された3D空間をもとに、移動ルート、クイズ、インタラクティブなオブジェクトなどを配置し、体験型コンテンツを構築できるプラットフォームである。 

TRANCITY Nebulaで管理される現場データを、Cesium ionを通じて大規模3Dデータとして最適化・配信し、Cesium for Unrealによって地理空間の文脈を保ったままUnreal Engine上のリアルタイム体験へ接続する。 

TRANCITY ARCADE：インフラデータを体験型アプリケーションへ 

従来のTRANCITYやTRANCITY Nebulaは、インフラの3Dデータを取得し、管理し、共有するための基盤として重要な役割を果たしてきた。現場を記録し、点群や3Dモデルを管理し、関係者が同じ空間情報を参照できるようにすることは、インフラデータ活用の出発点である。 

TRANCITY ARCADEの注目すべき点は、TRANCITY Nebulaで取得・管理・共有しているインフラデータを活用し、TRANCITY ARCADEと連携させることで、教育や体験のためのアプリケーションへ展開できる点にある。 

ARCADEでは、現場から取得された3Dデータを、単に閲覧する対象として扱うのではなく、利用者が目的に応じて体験を設計できる空間として扱う。再現された施設や現場の中に、移動ルートを設定する。特定の設備や危険箇所にクイズを配置する。視点を切り替えながら施設全体を理解する。インタラクティブなオブジェクトを通じて、紙資料やスライドでは伝わりにくい現場のスケール感や注意点を学ぶ。 

ここで重要なのは、「ゲーム化」そのものではない。インフラ現場における学習や教育は、単に知識を覚えることではなく、空間の関係性を理解し、状況を判断し、実際の行動に結びつけることが求められる。TRANCITY ARCADEは、現場データをそのような学びの場へ変えるためのアプリケーションである。 

橋りょう点検をテーマにしたゲーミフィケーションコンテンツ　 (提供：CalTa株式会社) 

J-POWERの現場で見えてきた、教育・安全・施設理解のユースケース 

TRANCITY ARCADEの実用性を示す例として、J-POWERにおける取り組みがある。発電所のような大規模インフラ施設では、現場を理解すること自体が簡単ではない。設備は広範囲に分散し、構造は複雑で、すべての場所を自由に見学できるわけではない。安全教育においても、実際のリスクを現場で体験させることには限界がある。 

J-POWERでは、発電所などのインフラ資産を対象に、CalTaと共同でCesium for Unrealを用いたゲーミフィケーションコンテンツの開発・検証を進めている。若手社員や新任者が、施設の全体像を早く理解する。。管理者が、設備や空間の関係性を直感的に説明する。こうした用途において、3D空間は、学習と判断を支える環境になる。 

安全教育の観点でも、このような体験型アプローチには大きな可能性がある。容易に現場へ行くことができない場所や、安全上立ち入りが制限される環境であっても、インタラクティブなクイズなどを通じて、状況理解や学習を行うことができるからである。単に手順を覚えるのではなく、「なぜ危険なのか」「どこに注意を向けるべきなのか」を体験を通じて理解できることは、安全意識の向上にもつながる。 

現実の現場で失敗することは許されなくても、体験空間の中では学ぶための試行錯誤ができる。普段は立ち入ることが難しいインフラ施設を、地域住民や一般のステークホルダーに分かりやすく伝える手段にもなり得る。インフラは社会に不可欠でありながら、その役割や仕組みが一般の人々には見えにくい領域である。 

現実世界の施設を地理空間の文脈を保ったまま体験できることは、インフラの専門家だけでなく一般の人々にとっても、施設や周辺環境への理解を深めることにつながる。Cesiumは、その文脈を維持しながら現実世界のデータをインタラクティブなアプリケーションへ接続することで、こうした体験を支えている。 

TRANCITY ARCADEは、産業向けの3D体験がどこへ向かうのかを示している。それは現実の施設、実際の業務、そこに関わる人々の学びや理解に寄り添うものである。より楽しく、より能動的に、より安全に学べる環境を作ることは、企業にとっても、そこで働く人々にとっても、地域社会にとっても意味がある。

J-POWER と CalTa が検証を進めているゲーミフィケーションコンテンツの画面イメージ（提供：J-POWER）

J-POWER と CalTa が検証を進めているゲーミフィケーションコンテンツの画面イメージ（提供：J-POWER）
Gamified content being developed and evaluated by J-POWER and CalTa. Courtesy J-POWER.

③動画（JPOWER QUESTのプレイ画面）

CalTaとキャドセンターがつなぐ、インフラ知見とリアルタイム3D実装 

この取り組みを支えているのは、CalTaとキャドセンターそれぞれの異なる強みである。CalTaはインフラ現場のデータと業務理解を持ち、キャドセンターはリアルタイム3D表現とインタラクティブな体験設計を実装する力を持っている。TRANCITY ARCADEでは、この二つの専門性がCesiumの地理空間技術と結びつき、現場データを実際に使えるアプリケーションへと展開している。 

やGoogle Photorealistic 3D Tilesのような技術検証、都市空間や施設空間の表現、インタラクティブな体験設計において、開発者としての実装力を持っている。 

CalTaが持つインフラデータ活用の知見と、キャドセンターが持つリアルタイム3D実装力は、 

Cesium ion：3Dデータのホスティング、タイル化、ストリーミングを行うプラットフォーム 

 3D Tiles：大規模な3Dデータを効率的かつ最適化された形で配信・利用するためのフォーマット 

Cesium for Unreal：ゲームエンジン上で3D地理空間エコシステムを活用可能にするプラグイン 

といったCesiumの技術と地理空間基盤の上で結びついている。 TRANCITY ARCADEのもう一つの特徴は、ノーコードアプローチにある。移動ルートやクイズ、インタラクティブなオブジェクトの配置を、専門的なゲーム開発の知識がなくても行うことができる。 

こうして、現場データ、地理空間技術、業務理解、体験設計が統合され、教育や訓練に活用できる産業向けアプリケーションが実現している。 

TRANCITYARCADEでのゲーミフィケーションコンテンツ作成状況　(提供：CalTa株式会社) 

TRANCITYARCADEでのゲーミフィケーションコンテンツ作成状況 (提供：CalTa株式会社) 
Gamified content being created in TRANCITY ARCADE. Courtesy CalTa Inc.

④動画（TRANCITYARCADEでゲーミフィケーションコンテンツ作成状況）

記録された現場から、学びと行動につながる空間へ 

3Dデータの価値は、記録や管理の中だけで完結するものではない。人が理解し、学び、判断し、行動できる形になったとき、その価値はさらに広がる。 

TRANCITY ARCADEは、インフラデータを「見る」ための3Dから、「使う」 

ための3Dへ展開し、教育、安全理解、施設理解といった具体的な業務価値を実現している。Cesiumは、現実世界の3Dデータを地理空間の文脈を保ったまま実用的なアプリケーションへつなぐ基盤を提供している。詳しくは Cesium ionを参照されたい。 

CalTa’s Trancity Arcade Turns Infrastructure Data into Spaces for Learning, Judgment, and Communication with Cesium for Unreal 

Across the infrastructure industry, organizations are increasingly capturing and managing real-world sites and facilities as 3D data. CalTa’s TRANCITY ARCADE uses Cesium ion, 3D Tiles, and Cesium for Unreal to create interactive applications for education, training, safety awareness, facility guidance, and communication. 

 A 3D model of a construction site used in gamified content. Courtesy CalTa Inc.

With point clouds, photogrammetry, 3D models, and Gaussian splatting, complex environments such as railways, power plants, urban spaces, and public facilities can be recreated in digital space with high fidelity. Teams use this data to understand the structure of a facility, grasp the relationship between different pieces of equipment, learn safety considerations, help younger engineers understand the full context of a site that is not easily accessible, or communicate the role and value of infrastructure to local communities and stakeholders. 

TRANCITY ARCADE, jointly developed by CalTa and CAD CENTER, extends infrastructure 3D data so people can learn, understand, communicate, and make better decisions in the field. Cesium-powered TRANCITY ARCADE is a platform for creating experiential content by placing routes, quizzes, and interactive objects within 3D spaces generated from real-world data, such as photographs, point clouds, and 3D Gaussian splatting. 

Site data managed in TRANCITY Nebula is optimized and streamed as large-scale 3D data through Cesium ion, then brought into a real-time Unreal Engine experience through Cesium for Unreal while preserving geospatial context. 

TRANCITY ARCADE: Turning infrastructure data into experiential applications 

TRANCITY and TRANCITY Nebula have played an important role as platforms for capturing, managing, and sharing infrastructure 3D data. Recording sites, managing point clouds and 3D models, and enabling stakeholders to refer to the same spatial information are foundational steps in making infrastructure data useful. 

What makes TRANCITY ARCADE noteworthy is that infrastructure data captured, managed, and shared through TRANCITY Nebula can be used in connection with TRANCITY ARCADE and extended into applications for education and experiential learning. 

In ARCADE, 3D data captured from the field is not merely something to view. Instead, it becomes a space where users can design experiences according to their purpose. Users set movement routes inside a recreated facility or site, place quizzes at specific equipment or risk points, switch viewpoints to understand the entire facility, and use interactive objects to learn scale, context, and safety considerations that are difficult to convey through paper documents or slides alone. 

The goal is not gamification itself. In infrastructure training and education, learning is about more than memorizing information; it requires understanding spatial relationships, recognizing situations, and connecting that knowledge to real-world action. TRANCITY ARCADE turns site data into this kind of learning environment.

Gamified content themed around bridge inspection. Courtesy CalTa Inc. 

Use cases for education, safety, and facility understanding at J-POWER 

A good example comes from J-POWER. At large-scale infrastructure facilities, like power plants, understanding the site itself is not easy. Equipment is distributed across wide areas, structures are complex, and not every location can be freely accessed. In safety education, there are also limits to what risks can be experienced directly in the field. 

J-POWER is working with CalTa to develop and evaluate gamified content using Cesium for Unreal for infrastructure assets, such as power plants. New employees and younger engineers can learn the full context of a facility more quickly. perspectives. Managers can explain relationships between equipment and spaces more intuitively. For these scenarios, 3D space becomes an environment that supports learning and judgment. 

Experiencing real-world facilities while preserving their geospatial context can help both infrastructure professionals and the public better understand facilities and their surrounding environments. Cesium helps make these experiences possible by connecting real-world data to interactive applications while maintaining that context.

This type of experiential approach has significant potential for safety training. Even in places that are not easy to visit in person, or environments where access is restricted for safety reasons, users can build situational understanding and learn through interactive quizzes and related experiences. Rather than simply memorizing procedures, users can understand through experience why something is dangerous and where their attention should be directed. Even when failure is not acceptable in the real world, an experiential space allows people to learn through trial and error. 

These experiences are not limited to internal training. They can also help communicate infrastructure facilities that are usually difficult to access to local communities and general stakeholders. Infrastructure is essential to society, but its role and mechanisms are often difficult for the public to see or understand. 

TRANCITY ARCADE offers a practical example of how industrial 3D experiences can be applied today, as experiences connected to real facilities, real work, and the real people who learn from and engage with them. Creating environments that make learning more engaging, active, and safe has value for companies, for the people who work there, and for the communities around them. 

Gamified content being developed and evaluated by J-POWER and CalTa. Courtesy J-POWER.

Connecting infrastructure expertise with real-time 3D implementation 

TRANCITY ARCADE brings together complementary strengths: CalTa’s infrastructure data expertise and CAD CENTER’s real-time 3D implementation capabilities. In TRANCITY ARCADE, these two areas of expertise are connected through Cesium’s geospatial technology to turn site data into a useful application. 

CalTa has worked on capturing, managing, and using site data in railway and infrastructure domains and provides a platform for handling infrastructure 3D data through TRANCITY Nebula. TRANCITY ARCADE is an extension of this work: it takes infrastructure data accumulated for management and visualization and extends it into applications for education and experience. 

CAD CENTER has long worked on 3D city models, digital twin visualization, and real-time 3D expression. It has implementation expertise in technologies such as Cesium for Unreal and Google Photorealistic 3D Tiles, as well as in spatial visualization, facility environments, and interactive experience design. 

CalTa’s knowledge of infrastructure data use and CAD CENTER’s real-time 3D implementation capabilities come together on a geospatial foundation built with Cesium: 

Cesium ion, the platform for hosting, tiling, and streaming 3D data; 

3D Tiles, the format for efficient and optimized data; and 

Cesium for Unreal, the plugin for unlocking the 3D geospatial ecosystem for game engines. 

Another key characteristic of TRANCITY ARCADE is its no-code approach. Routes, quizzes, and interactive objects can be configured without specialized game development expertise. 

With CalTa, CAD CENTER, and Cesium coming together in TRANCITY ARCADE, site data, geospatial technology, domain understanding, and experience design are integrated, enabling an industrial application for education and training. 

Gamified content being created in TRANCITY ARCADE. Courtesy CalTa Inc. 

From recorded sites to spaces for learning and action 

The value of 3D data expands when it reaches people in a form that supports understanding, learning, judgment, and action. 

TRANCITY ARCADE extends infrastructure data from “3D for viewing” to “3D for using,” creating concrete operational value in education, safety awareness, and facility understanding. Cesium provides the foundation for connecting real-world 3D data to practical applications while preserving geospatial context. 

Get started with your own Cesium ion account. 

インフラデータを、学び、判断し、伝えるための体験空間へ 

Over a decade ago, we showcased RikiTraki, a CesiumJS application built by Ricardo Morin for recording hiking trails. Ricardo was one of the first people to see the potential value of Cesium’s high accuracy 3D terrain rendering for outdoor sports. RikiTraki, a place to upload GPX tracks and photos from hikes, was largely a personal project, but Ricardo made it open to the public—and open source.

When Ricardo released RikiTraki 2.0, which now has hundreds of registered users, we caught up on his latest developments. New improvements to the site are a reflection of the significant investment Ricardo has put into the application; they’re also an illustration of how Cesium has evolved over the last ten years.

RikiTraki allows users to upload GPX tracks from their hikes, which they can review and share in 3D. Rendering on 3D terrain makes it easier to understand a hiker’s experience in the area. Courtesy Ricardo Morin.

RikiTraki 2.0 Tam McArthur Rim

All 3D: In 2015, visitors to RikiTraki would find a 2D world map built with Leaflet and the option to switch to Cesium for 3D. At the time, Ricardo felt that a 2D map was necessary for devices that didn’t have the compute power or support to run Cesium. Now, the entire site uses CesiumJS. With an always-3D view, users can seamlessly zoom in to individual trails or out for a global view. This shift was made possible by years of performance improvements by our CesiumJS team work at nearly every layer of the engine.

Efficient streaming: In its original form, RikiTraki loaded all available tracks at once, which became increasingly impractical as more users contributed data—a classic geospatial challenge. Ricardo solved this challenge by revising the app to request and display only the tracks relevant to the visitor's current view. This same principle is the foundation of 3D Tiles, the OGC community standard created by Cesium for streaming massive 3D geospatial datasets. Instead of downloading an entire dataset, 3D Tiles allows applications to efficiently stream only the portion of the world a user is looking at. And with the recent advancements in 3D Tiles 2.0, developers can now stream not just 3D models but also time-dynamic content, vector data, and continuous datasets with voxels, ensuring CesiumJS is ready for the next generation of global scale apps like RikiTraki.

Visitors to RikiTraki can explore GPX tracks near them. Courtesy Ricardo Morin.

Simplified layout: With the latest version of RikiTraki, side and bottom panels that provide more details, such as the elevation profile of a trail, open only as needed. CesiumJS has similarly advanced to offer a modular structure, giving developers access to what they need, when they need it. 

Personal data: RikiTraki was meant for sharing trails, and viewers have always been able to see paths in their area or across the world. Now, each visitor to RikiTraki also has a personal page to view, manage, and curate their own tracks separately from the public tracks. This dual approach to supporting personal data and offering access to global datasets is the philosophy behind Cesium ion, which allows CesiumJS developers to bring their own data for tiling as 3D Tiles or find global datasets like Google Photorealistic 3D Tiles.

Nambe Loop, New Mexico. For every trail on RikiTraki, visitors can view detailed information about the track. Courtesy Ricardo Morin.

Time dynamic visualization: RikiTraki doesn’t just show a hiker’s entire path at once: an animation draws the route, with the camera tracking the position along the route as it gets drawn. This allows hikers to relive their treks. 4D visualization is a core component of CesiumJS, drawn from our roots in aerospace, that makes Cesium valuable for understanding temporal spatial data. 

3D terrain: CesiumJS has always been 3D first, and from its inception RikiTraki provided visitors with 3D terrain that gave them an intuitive understanding of their hikes. The site originally used elevation values from GPS devices, which were often uncalibrated or inconsistent, so track elevation is now sampled directly from the terrain. The elevation profile of a track gives viewers a quick understanding of the course of the path. High quality terrain in CesiumJS isn’t just for looks: it’s a critical foundation that allows many in our community to perform measurements and analysis.

Trillium Falls, California. RikiTraki places geolocated photos from hikers’ treks at the appropriate spots on the trail. Courtesy Ricardo Morin.

Easy sharing: RikiTraki has always been publicly available on the internet and easy to share with a link. In the newest version, URLs are simple and predictable, clearly listing the user name to link to a personal space, the lat/lon to show a location, or a track ID for a specific trail. Likewise, CesiumJS endures as an accessible, secure way to share your geospatial data.

Open source: Ricardo’s work, like CesiumJS itself, is open source and on GitHub. Ricardo documents the site’s architecture and updates on his blog, and he has contributed in the past to Cesium learning materials. We encourage all members of the CesiumJS community to be active contributors to CesiumJS and the community forum.

"My work has always been open source. For me, it feels good to give something back to the community. If other developers want to see how I built RikiTraki or fork the project and build their own app, they can. That's the strength of an open source community." 

For more than ten years, RikiTraki has provided a way to visualize, remember, and share outdoor experiences. We’re proud of the apps our community builds with CesiumJS and committed to continuously improving the tools you use: subscribe to the release roundup thread on the Cesium forum to get monthly notifications of new releases.

RikiTraki’s Hiking Tracks on the Web Evolve Alongside CesiumJS

人工衛星が取得するデータ量は急速に増大している。将来的には、地球観測衛星だけでも1日あたりペタバイト級のデータが生成されるとも予測されている。こうした膨大なデータをすべて地上に送信してから処理する従来の方式では、通信帯域や地上局数の制約から限界に近づきつつある。 

こうした課題に対し、NTTソフトウェアイノベーションセンタでは「宇宙データセンタ」と呼ばれるコンピューティングアーキテクチャの研究開発が進められている。この取り組みでは、人工衛星上でAI推論などのデータ処理を実行し、重要な情報のみを地上に送信することで、通信効率の向上と迅速なデータ活用を目指している。 

このアーキテクチャの設計や検証を支える可視化の試みとして、Webベースの3D地球可視化エンジンであるCesiumJSが活用されている。

宇宙でAIが動く新しいデータ処理モデル 

その中核の一つとなるのが、衛星軌道および衛星間通信リンクを統合的にシミュレーションできる基盤である。 

従来の地球観測ワークフローは、次のような流れで構成されていた。 

これに対し、NTTが検討している新しいモデルでは、 

重要な情報のみを地上へ送信 
という処理アーキテクチャが採用されている。  

NTTの技術展示イベント「NTT R&Dフォーラム2025」で公開されたデモでは、人工物検知アルゴリズムを用いて重要領域のみを抽出することで、送信データ量を約96%削減できる可能性が示された。 

ハイパースペクトルデータ（疑似RGB画像）: 衛星上で取得された観測データ（ハイパースペクトルデータ）の可視化例。（提供：NTT）

AI処理による重要領域抽出結果（データ削減後）: 同データに対してAI処理を適用し、重要または異常と判断された領域のみを抽出した例。（提供：NTT）

このアプローチは単なる通信効率の改善にとどまらない。 
限られた通信帯域の中で「どの情報を優先して地上へ送るか」を選別できるため、 

インフラの異常検知 
といった迅速な判断が求められる分野での応用が期待されている。  

宇宙データセンタのアーキテクチャでは、単一の衛星ではなく、複数の要素が連携する分散システムが想定されている。 
例えば次のような要素が同時に関係する。 

時間とともに変化するネットワーク構造  

宇宙データセンタの概念を可視化したもので、衛星上でのデータ処理の様子を示している。（提供：NTT） 

Visualization of a space data center concept, showing satellite-based processing in orbit. Courtesy NTT. 
宇宙データセンタの概念を可視化したもので、衛星上でのデータ処理の様子を示している。（提供：NTT）

NTT: space data center concept

NTTでは、宇宙データセンタを構成する衛星群の軌道や通信リンク、軌道上でのAI処理を統合的にシミュレーションできるライブラリも開発している。しかし、衛星数やシミュレーション期間が増えるにつれて、可視化処理の負荷が増大し、研究環境の制約になるケースも見られた。 

この課題に対し、NTTでは大規模な軌道シミュレーションのための可視化環境の構築・検証にCesiumJSを用いた。 

CesiumJSを用いた宇宙システムの可視化 

NTTが可視化の選択肢を比較検討する中で、CesiumJSのいくつかの特徴が有効であることが分かった。 

CZMLによる時間変化を伴うオブジェクト表現 
衛星軌道や通信リンクを自然に表現できる  

Webブラウザ上での高性能レンダリング 
大規模シミュレーションでも操作性を維持できる  

地理空間データとの統合 
地形や衛星画像と組み合わせて地球上の文脈で理解できる  

CesiumJSを用いることで、衛星の軌道、通信リンク、観測対象地点などを3D地球上で直感的に把握できる可視化環境が実現された。 

分散ネットワークアーキテクチャにおける衛星間通信リンクの可視化。（提供：NTT） 

Inter-satellite communication links visualized in a distributed network architecture. Courtesy NTT. 
分散ネットワークアーキテクチャにおける衛星間通信リンクの可視化。（提供：NTT）

NTT: inter-satellite communication links

また、Cesium ionの地理空間データを組み合わせることで、宇宙空間の挙動と地球上の観測対象を同時に把握することが可能になっている。

可視化・分析レイヤとしてのCesium 

本プロジェクトにおいて、Cesiumは可視化および分析のレイヤーとして機能する。 

オンボード処理パイプラインの構築や、前処理・AI推論フローの設計を担っているのは、NTTが開発した low-code / no-code のパイプライン設計ツールである。 

CesiumJS は、そうした処理構成や実行結果を3次元空間上で可視化・分析するためのレイヤとして機能している。衛星軌道、通信リンク、観測地点、センサー由来データやAI推論結果を地形やインフラと統合して表示することで、研究者やエンジニアはシステム全体の挙動を直感的に把握できる。 

Cesiumはパイプラインを「設計する」ためのインタフェースではない。一方で、複雑な宇宙分散システムがどのように振る舞っているかを“観測可能”にし、仮説検証や異常の発見、関係者間での認識共有を支援する。 

このようにCesiumは、NTTの設計ツール群と連携しながら、研究開発を加速する可視化・分析基盤として重要な役割を果たしている。 

研究開発を加速する可視化基盤 

可視化部分をCZMLベースの構成に整理したことで、ソフトウェア構成はシンプルになり、開発効率も向上した。 
その結果、研究チームは開発開始から約2か月でプロトタイプをNTT R&Dフォーラムに展示することができた。 

可視化の実装やレンダリング最適化にかかる負担が軽減されたことで、研究者はより多くの時間を、軌道計算や通信リンク成立判定、分散処理アーキテクチャ設計などの宇宙データセンタの実現に向けた中核機能の研究開発に集中できるようになった。 

現在のプロトタイプでは、主にCZMLを用いた衛星軌道や通信リンクの可視化が中心となっている。将来的に衛星コンステレーション規模が拡大し、より大規模なデータ可視化処理が必要になった場合には、3D Tilesなどの階層的ストリーミング技術の活用も検討されている。 

宇宙で処理し、地上で理解する。その橋渡し役として、空間可視化技術の重要性は今後ますます高まっていくだろう。 

Cesiumでは、NTTのように新しい宇宙コンピューティングアーキテクチャを探求する組織が、複雑なシステムを理解し共有するための基盤としてCesiumを活用していることを嬉しく思います。 

他の航空宇宙企業のCesium活用例についてもぜひご覧ください。 

NTT Explores a Space Data Center Architecture with Cesium for On-Orbit AI and Satellite Network Visualization

The volume of data collected by satellites is increasing rapidly. In the future, even Earth observation satellites alone are expected to generate data at the petabyte-per-day scale. Under the conventional approach of transmitting all of this data to the ground before processing, limitations in communication bandwidth and the number of available ground stations are becoming increasingly significant. 

To address this challenge, NTT Software Innovation Center is conducting research and development on a computing architecture referred to as the “Space Data Center.” In this approach, data processing such as AI inference is executed onboard satellites, and only important information is transmitted to the ground, with the goal of improving communication efficiency and enabling faster use of data. 

As part of the effort to support the design and validation of this architecture, NTT is using CesiumJS, a web-based 3D globe visualization engine. 

A new data processing model in which AI operates in space 

One of the core elements is a platform capable of integrated simulation of satellite orbits and inter-satellite communication links. 

A conventional Earth observation workflow has typically consisted of the following steps: 

A satellite observes Earth’s surface.  

Analysis and processing are performed on Earth.  

By contrast, in the new model being explored by NTT, the processing architecture is: 

Only important information is transmitted to the ground.  

In a demonstration presented at NTT’s technology showcase event, NTT R&D Forum 2025, an object-detection algorithm was used to extract only important regions, showing the possibility of reducing transmitted data volume by approximately 96%. 

Hyperspectral data (pseudo-RGB visualization): Example of observation data (hyperspectral data) acquired onboard a satellite, visualized as a pseudo-RGB image. Courtesy NTT. 

AI-processed result highlighting regions of interest (after data reduction): Example of applying AI processing to the same dataset, extracting only regions identified as significant or anomalous. Courtesy NTT. 

This approach is not limited to improving communication efficiency alone. 

Because it makes it possible to select which information should be prioritized for transmission to the ground within limited communication bandwidth, it is expected to be applicable in fields requiring rapid decision-making, such as: 

A distributed system expanding into space 

The Space Data Center architecture assumes not a single satellite but a distributed system in which multiple elements work together. 

For example, the following elements are involved simultaneously: 

network structures that evolve over time.  

Visualization of a space data center concept, showing satellite-based processing in orbit. Courtesy NTT. 

NTT has also developed a library capable of integrated simulation of the satellite orbits, communication links, and onboard AI processing involved in the Space Data Center. However, as the number of satellites and the simulation duration increased, the computational load of visualization also increased, becoming a constraint in the research environment in some cases. 

To address this issue, NTT conducted development and validation of a visualization environment using CesiumJS for large-scale orbital simulations. 

Visualizing space systems with CesiumJS 

As NTT evaluated different visualization options, several characteristics of CesiumJS proved effective: 

Object representation with temporal changes using CZML: 
Orbital paths and communication links can be represented naturally.  

High-performance rendering in a web browser: 
Operability can be maintained even in large-scale simulations.  

Integration with geospatial data: 
Space systems can be understood in the context of Earth by combining them with terrain and satellite imagery.  

By using CesiumJS, NTT created a visualization environment in which satellite orbits, communication links, and observation target locations can be intuitively understood on a 3D globe. 

Inter-satellite communication links visualized in a distributed network architecture. Courtesy NTT. 

In addition, by combining it with geospatial data from Cesium ion, it becomes possible to understand space-based behavior and Earth-based observation targets at the same time. 

In this project, Cesium plays a central role as a visualization and analysis layer. 

NTT’s low-code/no-code pipeline design tool provides the primary interface for configuring onboard processing workflows, including preprocessing steps and AI inference pipelines. 

CesiumJS serves as the visualization and analysis layer that complements this design environment. By visualizing system configurations, sensor data, and processing outputs in a unified 3D context, Cesium enables researchers and engineers to intuitively 

inspect, validate, and reason about complex onboard behaviors more effectively. 

Rather than acting as a pipeline authoring interface, Cesium focuses on making system behavior observable.   

This visualization-driven analysis shortens iteration cycles by helping researchers identify anomalies, evaluate assumptions, and communicate findings across interdisciplinary teams. In this way, Cesium provides a foundational layer that accelerates R&D while integrating seamlessly with NTT’s broader toolchain. 

A visualization foundation that accelerates R&D 

By reorganizing the visualization component into a CZML-based structure, the software configuration became simpler and development efficiency improved. 

As a result, the research team was able to demonstrate a prototype at NTT R&D Forum, in approximately two months from the start of development. 

By reducing the burden associated with visualization implementation and rendering optimization, researchers were able to spend more time focusing on the research and development of core functions required to realize the Space Data Center, such as orbital calculations, communication link validation, and distributed processing architecture design. 

In the current prototype, visualization mainly focuses on satellite orbits and communication links represented using CZML. In the future, as satellite constellation scale increases and larger-scale visualization processing becomes necessary, the use of hierarchical streaming technologies such as 3D Tiles is also being considered. 

Process in space, and understand on Earth. As a bridge between the two, the importance of geospatial visualization technology is expected to grow even further. 

At Cesium, we are pleased to see organizations like NTT—exploring new space computing architectures—use Cesium as a foundation for understanding and sharing complex systems. 

Please also explore how other aerospace companies are using Cesium. 

 Cesiumで可視化する軌道上AIと衛星ネットワーク ――  NTTが探る「宇宙データセンタ」アーキテクチャ

Lu Zhang is perhaps not the only person who sometimes finds running on a treadmill monotonous. During a recent workout he thought how much nicer it would be to run through some of the neighborhoods he used to live in. Since a quick flight to Paris or Shanghai for a run wasn’t realistic, he asked an AI chatbot a simple question: was it possible to recreate real-world neighborhoods in an immersive environment? That was the first time he’d heard of Cesium.

With EarthRunner, Lu is able to take his treadmill runs to cities all over the world. Courtesy Lu Zhang.

As a neuroscientist, Lu has studied spatial navigation—how the brain combines self-motion with external landmarks to represent and move through the world. With AI tools as a learning and prototyping partner, he brought that neuroscience background into geospatial technology and created EarthRunner.

The Parthenon in Google Photorealistic 3D Tiles. With Cesium for Unreal, runners can explore revisit familiar places or explore new areas. Courtesy Lu Zhang.

EarthRunner lets users run through a full-scale 3D world of real places, built with Cesium for Unreal streaming Google Photorealistic 3D Tiles. Locomotion is controlled by the treadmill, and an accompanying iPad interface, created with Python, handles navigation.

A chance to run in familiar cities made workouts more engaging. Lu further enhanced the experience with an AI-powered audio guide that highlights points of interest, making it easy to get to know new places. While EarthRunner remains a personal project, Lu sees possibilities far beyond his own workouts.

An AI-powered audio guide highlights points of interest. Courtesy Lu Zhang.

“AI gave me the confidence to try something completely new with Cesium for Unreal. Seeing the world appear almost exactly as I remembered it from my travels was completely amazing. And when I moved beyond experimenting, the Cesium documentation made it much easier to really understand the platform. After that, it felt like a whole new world opening up.” 

Lu may not have known about Cesium before he began this project, but it enabled him to take an idea sparked during a workout into an application that surpassed his original goals. Lu is now a Cesium Certified Developer, a testament to how accessible 3D geospatial development can be with the right resources. If you’re new to Cesium for Unreal, check out our tutorials to get started building your own custom application with global 3D datasets.

Bringing Earth to the Treadmill with Cesium

For industries managing vast linear infrastructure like railways and power lines, safety and reliability are paramount—and ensuring that safety requires constant monitoring and analysis of immense volumes of data. The Cross Product, a software development company specializing in LiDAR data processing, addressed this challenge by creating TCP Studio, a 3D visualization platform built with Cesium.

TCP Studio V9

From raw data to a custom visualization platform

The Cross Product recognized a critical gap in their users’ workflows: while TCP could process massive point clouds to extract meaningful information, users often lacked the specialized tools to visualize and interact with these rich datasets. This was a barrier to turning processed data into timely, actionable insights for infrastructure management.

To bridge this gap, The Cross Product developed TCP Studio, a SaaS solution built from the ground up using CesiumJS. The Cross Product also converts LAS point clouds into 3D Tiles via Cesium ion’s tiling pipeline. “Previously, we assumed clients had their own visualization tools, which was only partially true,” explained Elise Vi Nhu Ba, R&D engineer at The Cross Product. “A dedicated interface is now a significant advantage, allowing us to showcase our solutions’ capabilities through a custom-built environment with full control over the UX.”

インフラデータを、学び、判断し、伝えるための体験空間へ

RikiTraki’s Hiking Tracks on the Web Evolve Alongside CesiumJS

Cesiumで可視化する軌道上AIと衛星ネットワーク ―― NTTが探る「宇宙データセンタ」アーキテクチャ

Bringing Earth to the Treadmill with Cesium

The Cross Product Transforms Raw LiDAR Data into Actionable Infrastructure Insights with Cesium

Geotour Showcases Crete with Synchronized Panoramas and Video in CesiumJS

Purdue University Exploring the Boundaries of XR with Cesium