Cesium for Omniverse v0.24.0

Cesium for Unity Samples v1.13.1

CesiumJS 1.123

Climate & Environment

It’s wildland fire season in the United States. The Lockheed Martin AI Center’s (LAIC) Joint Activity Manager (JAM) provides operational context for active wildland fires, using AI, real-time data, and CesiumJS to stream this 3D visualization to incident commanders.

Overview of Lockheed Martin JAM capability, featuring a sped-up clip of the Vista fire outside of Los Angeles, California. Courtesy Lockheed Martin.

Overview of Lockheed Martin JAM capability, featuring a sped up clip of Vista fire outside of Los Angeles, CA. Courtesy Lockheed Martin.

Lockheed Martin JAM - Vista, CA, July 2024

While still in development, this capability is intended for state agencies to visualize and analyze active wildland fires; track flights of aerial assets that have been tasked with detection, monitoring, and suppression; and incorporate weather information, such as temperature, humidity, and wind.

The wildland fire incident list in the application is populated every 24 hours with information from the National Interagency Fire Center (NIFC), based in Boise, Idaho, USA, to ensure daily updates on the number and locations of active wildland fires. Imagery from National Oceanic and Atmospheric Administration’s (NOAA) Geostationary Operational Environmental Satellites (GOES) is pulled every 30 minutes. 

In an upcoming feature, Lockheed Martin’s AI will detect near-real-time fire hot spots from this imagery and reflect them atop 3D terrain from Cesium every 15-20 minutes. Lockheed Martin uses its “super resolution” AI capabilities to, in effect, add more pixels to the images, which refines them prior to determining the near-real-time fire area from the satellite imagery.

Tracking a Pilatus PC-12 on patrol identifying and mapping wildland fires in CesiumJS. Courtesy Lockheed Martin.

JAM brings together ground, air, and satellite data from NIFC, NOAA, and ADS-B flight trackers (as seen in the image above) and combines them in CesiumJS. State agencies might also have their own assets (e.g., thermal imaging from multi-mission aircrafts) that can be added. The application uses Cesium World Terrain and Bing Maps Aerial imagery streamed as 3D Tiles via Cesium ion, to provide incident commanders and staff an accurate 3D map to enhance the common operating picture. CesiumJS was built for interactive web apps and streaming massive amounts of data—it is lightweight and performant, vital for users receiving rapid updates in the field.

Work on the JAM prototype began in December 2023, and efforts on the current demo started in March 2024. Lockheed Martin, which employs 122,000 people worldwide, assigned five developers on this project. The company selected Cesium and its real-time update capabilities as an efficient, effective tool for visualizing historical wildland fire data. Lockheed Martin continues to leverage commercial partnerships to accelerate development of JAM.

Wind and weather information for an active fire area in CesiumJS. Courtesy Lockheed Martin.

Demo of suppression line visualization in CesiumJS. Courtesy Lockheed Martin.

The crew behind JAM is working toward including all active wildland fires in the US. The alpha version was completed in May 2024, and beta is slated for this summer.

You can fuse your own data with high-resolution terrain and imagery with Cesium ion; get started with a community account.

Lockheed Martin Tracks Wildland Fires with Cesium

To introduce students to the space industry, New Ascent launches “ChipSats” to gather environmental info and tracks their descent in 3D as part of MISSION: SubSpace, an in-classroom aerospace mission experience that uses an interactive web portal built on CesiumJS.

Students get their own mission control experiences with MISSION: SubSpace. Courtesy New Ascent.

Students get their own mission control experiences with Mission: SubSpace, powered by CesiumJS. Courtesy New Ascent.

Misson: SubSpace by New Ascent

New Ascent is a STEM education company, focusing on the impacts of the space industry on daily life by engaging students in grades 3-12 in real science missions. MISSION: SubSpace was released in 2023 to show young learners that they can be involved in space without being an astronaut. 

This educational experience uses ChipSats—among the smallest spacecraft, fitting into an adult human’s hand—originally developed by Cornell University and armed with sensors and radio comms. Today, New Ascent uses drones to take the ChipSats up to altitude (usually about 2-4 miles above Earth) and release them. In the future, they plan to use an in-house-developed launch system to deploy at heights above weather balloons (about 10-20 miles above Earth) but below satellites (minimum 100 miles above Earth).

As the ChipSats descend above Spaceport America in Truth or Consequences, New Mexico, USA, MISSION: SubSpace populates with figures from the ChipSats, allowing students to visualize the accurate locations of their own tiny satellites in 3D and observe and analyze temperature, pressure, and other data. 

“We want to get kids involved with highly engaging tools. Visuals are huge in learning, especially STEM. The centerpiece of the portal is the 3D visualization using Cesium; it’s not just points on a map anymore,” said co-founder and CEO Rob Quigley.

New Ascent’s ChipSats are approximately 4 inches by 1 inch by 1/4 inch. US quarter for scale. Courtesy New Ascent.

As the ChipSats hurtle down through our atmosphere, they transmit and store environmental data, which is then packaged as a CSV file. This time-series data is combined with high-resolution real-world terrain and imagery from Cesium World Terrain and Bing Maps Aerial imagery via Cesium ion, streamed as 3D Tiles to CesiumJS on student laptops, which are often not as robust as those of professionals. Although the ChipSats descend in New Mexico, classrooms anywhere can access CesiumJS-powered MISSION: SubSpace. Quigley reports he has had more than 120 students signed into the web portal at once, each with their own mission control experience, observing and analyzing time-dynamic data.

MISSION: SubSpace has used CesiumJS from the start, as Quigley had relied on it for trajectory visualization for a different project years ago. With Cesium’s accuracy and ease of use, Quigley knew it would be right for students with varying degrees of tech savvy. 

“Using Cesium let us get the portal going in a matter of weeks vs. months,” said Quigley.

ChipSats transmit data about their journeys through Earth’s atmosphere, replayed for and analyzed by students using CesiumJS. Courtesy New Ascent.

New Ascent is working toward near-real-time data visualization for MISSION: SubSpace and plans to include other launch sites, including international locations, as they inspire the next generation of aerospace professionals.

Explore how students and researchers are learning about our planet and beyond with Cesium.

New Ascent Brings Space to Students with CesiumJS

日本最大の都市住民の「生活の質の向上」を守る

デジタルツインのリアルタイム可視化を３D地理空間技術で支えるCesium

「東京都デジタルツイン3Dビューア」では、３D都市モデルに加え、都市における３D点群データや都営バスの位置情報、河川データ、様々な２Dデータや動画などを重ね合わせた可視化を行う事ができます。その３Dビューアの可視化基盤となって利用されているのがCesiumJSとCesium ionです。　

東京都のデジタルツイン データを単一のポータルで

「東京都デジタルツイン3Dビューア」

　1,400万人を超える日本最多の住民を抱える東京都は、デジタルの力で東京のポテンシャルを引き出し、都民の生活の質の向上（クオリティ・オブ・ライフ：Quality of Life、以下QoL）のため、東京都全体のデジタルツインの社会実装を目指しています。都庁は都市のデジタルツインを3つの柱、「データ整備」「データ可視化」「データ解析」と定義、この３つの柱を３D地理空間プラットフォームの活用で連携させ、利用者に最も体験を提供しやすい「データの可視化」に先駆けて取り組みました。「データの可視化」は、都民や企業、各行政を含めた利用者とともに都市を創っていくために必要な共通認識や合意形成を図るうえで非常に重要と判断したからです。その結果、2021年に都庁のデジタルツインの世界を３D地理空間情報の可視化で体現する「東京都デジタルツイン3Dビューア」を生み出し、現在では自治体を超えた多くの行政・企業・市民からの利用が進んでいます。ここで３Dビューアの基盤として利用されているのがCesiuｍプラットフォームです。

Cesiumは海外諸都市ですでに利用実績も多く、CityGMLやLASといった様々な3Dデータ形式を3Dタイルに変換しストリーミング用に最適化し、属性データを保持して可視化できる点、グローバルレベルで地形、画像、写真測量データなど実世界の３Dコンテンツが豊富な点、Web上で可視化され誰でも利用できる点、などが評価され採用されました。

さらに、大量の点群データの3Dタイルへの変換は、すべてCeisum ionのタイル変換機能が利用されています。また、庁内環境の地形データ配信を行うCesium ion Asset Serverや、外部へのデータ公開もCesium ionで実現されています。

点群データ（伊豆大島）＋ 離島港湾ライブカメラ

これらのリアルタイム情報をさらに都民への迅速で正確なサービスに繋げるため、都庁内DXの一環として庁内に分散していた様々な形式の地理空間データの整備を進め、庁内・庁外のリアルタイムデータのCesiumベースでの３Dビューアへの反映と、各種サービスの創出につなげています。

高精度の視覚化・リアルタイムデータをもとに、利用者とインタラクティブに創造する都市づくりを目指す

現在Cesiumの利用をもとに、東京都デジタルツイン3Dビューアでは、地形データが25cm精度の詳細なものとなっており、日本のジオイド2011に基づいて変換しているため、高い垂直方向の精度を実現しています。また、自動車のセンサーデータ、交通量調査ビデオからAI解析した交通量データの可視化を官民で試行しています。

さらに、災害多発国日本での都市のQoLを守るため、最大の注力領域の一つである防災分野では、防災に関するリアルタイムデータを充実させ、災害発生時に都外の他の地域にも及ぶ広域支援も実施しています。 

例えば水害時には、予想される氾濫時の浸水エリア、海の近くでは高潮による被害想定、地形データ、避難所などの情報を一元的に可視化し防災対策を立てやすくしています。また、実際の豪雨時には、河川のリアルタイムデータ(水位、雨量、ライブカメラ、警報の発令状況)、高潮に関するリアルタイムデータ（水門付近の水位、ライブカメラ）を一元的に可視化、発信することで、都民が迅速に現状把握し、早めに避難行動に移れるようにしています。

水防災情報システム 水位データ＋河川監視カメラ＋浸水想定区域図

様々な可視化を実現しインタラクティブなサービスを目指す

また、日本は世界有数の地震の多発国ですが、東京都として、今回の能登半島地震で被災前のデータと被災後のデータを掲載することで早期の復興対策を支援しています。測量のもとになる精緻なデータとして緯度・経度・高さ・色情報を有する点群データを使用し、被災前の点群データやそれをもとにした地形データを３Dビューアに掲載、被災後の斜面崩落に関するデータと重ね合わせることで、被害状況の把握や復旧・復興活動の迅速化を支援するものです。

東京都庁は、日本における3D地理空間情報の第一線の使い手として、「東京都デジタルツイン3Dビューア」をデジタルツイン実現の軸と位置づけ、都市の災害に対する強靭化や都民のQoLの向上をさらに進化させ続けています。私たちCesiumは、東京都庁のこのような取り組みを支援できたことを誇りに思います。

CesiumJS を使用して独自のインタラクティブな Web アプリを構築するには、ラーニング　センターのガイドをご参照ください。また、Cesium ionを使用すると、世界中の地形、画像、建物を含む実物大の地球に独自のデータを取り込むことができ、Cesiumの 3D タイル パイプラインは、データセットの大きさに関係なく、ストリーミング用にデータを最適化します。ぜひ無料のCesium ionアカウントにサインアップしてお試しください。また、独自の環境で3Dコンテンツの作成とホスティングを開始する場合はCesium ion Self-Hostedサービスを是非トライしてみてください。

Tokyo Metropolitan Digital Twin 3D Viewer Uses Cesium to Improve Quality of Life for Residents

"The Tokyo Metropolitan Digital Twin 3D Viewer” enables overlaying various types of data, including 3D city models, 3D point cloud data within the city, location information of Tokyo Metropolitan buses, river data, various 2D data, and videos, in addition to the 3D city model. CesiumJS and Cesium ion are utilized as the visualization infrastructure for that 3D viewer.

Digital twin data for Tokyo city in a single portal

Tokyo, which has the largest number of residents in Japan with over 14 million people, aims to unleash Tokyo's potential through the power of digital technology, and to achieve the social implementation of a digital twin for the entire Tokyo metropolis, aiming to improve the quality of life (QoL) for its residents. 

The Tokyo Metropolitan Government (TMG) has defined three pillars for the city's digital twin: "data organization," "data visualization," and "data analysis." It has proactively addressed "data visualization," which offers users the most accessible experience, by integrating these three pillars through the utilization of a 3D geospatial platform. This is because the TMG has deemed "data visualization" to be extremely important in fostering a common understanding and consensus among users, including citizens, businesses, and various administrative entities, in order to collectively shape the city. As a result, in 2021, the TMG created the 'Tokyo Metropolitan Digital Twin 3D Viewer,' which embodies the world of the metropolitan government's digital twin through the visualization of 3D geospatial information. Currently, there is increasing utilization of this viewer from a wide range of administrations, businesses, and citizens beyond municipal boundaries. The Cesium platform serves as the foundation for this 3D viewer.

Cesium has been widely adopted in various cities overseas, with numerous successful implementations. It is praised and adopted for its ability to convert various 3D data formats such as CityGML and LAS into 3D Tiles, optimizing them for streaming while retaining attribute data for visualization. Additionally, its rich availability of real-world 3D content such as terrain, imagery, and photogrammetry data at a global level, along with its accessibility for visualization on the web, has been recognized and embraced as well.

Furthermore, the conversion of large point cloud data into 3D Tiles is all handled by Cesium ion's tile conversion functionality. In addition, Cesium ion Asset Server, which delivers terrain data for the interior environment of the TMG, and external data publication is executed through Cesium ion.

Point cloud data (Izu Oshima) + Remote island port live camera.

As part of the TMG's internal digital transformation efforts, various formats of geospatial data dispersed within the government offices are being organized to further connect real-time information to swift and accurate services for the citizens. This initiative aims to reflect both internal and external real-time data onto a 3D viewer based on Cesium, facilitating the creation of various services.

Aiming to create cities interactively with users based on high-precision visualization and real-time data

Currently, based on the use of Cesium, the Tokyo Digital Twin 3D Viewer has detailed terrain data with an accuracy of 25 cm, this precision is achieved through conversion based on Japan's geoid 2011, ensuring high vertical accuracy. In addition, the public and private sectors are experimenting with visualizing traffic volume data analyzed by AI from vehicle sensor data and traffic survey videos.

Furthermore, in one of the major focus areas, disaster prevention, which is crucial for maintaining the quality of life in disaster-prone Japan, efforts are being made to enhance real-time data related to disaster prevention. Additionally, broad-scope support extending to other prefectures is being provided in the event of disasters.

For example, during floods, we visualize various information such as anticipated inundation areas during expected flooding, damage estimates due to high tides near the sea, terrain data, and shelter locations in a unified manner, making it easier to plan disaster prevention measures. Additionally, during actual heavy rainfall, the 3D viewer unifies and visualizes real-time river data (water levels, precipitation, live camera feeds, status of warnings) and real-time data related to storm surges (water levels near floodgates, live camera feeds). This enables citizens to quickly understand the current situation and take earlier evacuation actions.

Water disaster prevention information system: Water level data & River monitoring camera & Expected flooding area map.

Aiming for interactive services by realizing various visualizations.

Furthermore, as Japan is a country prone to frequent earthquakes, the TMG is aiding in early recovery efforts by publishing data before and after the Noto Peninsula earthquake. Using point cloud data containing precise information such as latitude, longitude, height, and color, which serves as the basis for surveys, the TMG is posting pre-disaster point cloud data and the derived terrain data on the 3D viewer.　By overlapping this data with data related to subsequent slope collapses, this will assist in understanding the damage situation and speeding up recovery and reconstruction activities.

The TMG positions the "Tokyo Metropolitan Digital Twin 3D Viewer" as a cornerstone of digital twin realization, serving as a leading user of 3D geospatial information in Japan. Continuously evolving, it aims to further enhance disaster resilience and improve the quality of life for citizens in the city. We at Cesium are proud to have supported the Tokyo Metropolitan Government in such endeavors.

To build your own interactive web application using CesiumJS, please refer to the Learning Center. Cesium ion also allows you to incorporate your own data into a full-scale globe, including terrain, imagery, and buildings from around the world. Cesium's 3D Tiling Pipeline optimizes data for streaming regardless of dataset size. Feel free to sign up for a Cesium ion account. Or you can request a Cesium ion Self-Hosted evaluation to begin creating and hosting 3D content in your own environment.

東京都デジタルツイン3Dビューアは Cesiumを活用し、「都民生活の質の向上」を守る

Fluid Planet is bringing Canadian provincial parks and other locations around the world to young students, aiding their ecological exploration with virtual field trips using Cesium for Unreal and Google Maps Platform's Photorealistic 3D Tiles.

Writing-on-Stone Provincial Park, Alberta, Canada, in Cesium for Unreal. Courtesy Fluid Planet.

Fluid Planet brings Canadian provincial parks and other locations around the world to young students, aiding their ecological exploration with virtual field trips using Cesium for Unreal.

Fluid Planet

Calgary-based Fluid Planet’s science education platform is geared primarily toward grade-school children. In addition to delivering traditional lessons, teachers can take their young learners safely through protected lands and various ecosystems locally and far from home through realistic interactive games. Students roam habitats to learn about animals, changing the setting with their choice of weather and lighting or syncing to reflect current conditions.

While whimsical graphics can engage users, Fluid Planet’s director, Dan Pigat, explained that staying true to a location’s flora, fauna, and geographic features provides accurate, actionable information, especially when travel is not practical or possible. Elementary students, for example, might learn where a fox lives and what it eats, while high-schoolers could follow the length of a river and predict environmental impacts.

Fluid Planet has combined airborne and terrestrial lidar data from the University of Lethbridge, BIM models, Cesium World Terrain, and Bing Maps Aerial imagery to share real-world experiences in 3D. Locally collected data is paired with global geospatial context to seamlessly show our planet how it really is. With Cesium for Unreal, massive datasets are hosted in Cesium ion, tiled into 3D Tiles, and streamed to Unreal Engine. Fluid Planet is also integrating Photorealistic 3D Tiles, with data available in 49 countries, via Google Maps Platform’s Map Tiles API. The PureWeb plugin for Unreal enables pixel streaming so that student devices (which often have limited capabilities) can interact with Fluid Planet remotely and concurrently in a browser.

Students direct a fox to explore the Canadian Rocky Mountains. Courtesy Fluid Planet.

Pigat’s college interns are also working on locations for and with Indigenous peoples, including digitally rebuilding a Blackfoot village by examining old maps and detecting tipi rings in lidar data. Fluid Planet’s platform can support education outside of schools, too, in training employees on digital twins prior to arriving at job sites.

Teachers received beta access to Fluid Planet in July 2023; the app will be available to Canadian students in early 2024 and accessible to all shortly thereafter. 

You can combine your data with curated global 3D assets by signing up for a free Cesium ion account.

Fluid Planet Immerses Young Students in the Outdoors with Cesium for Unreal and Photorealistic 3D Tiles

Re:Earth by Eukarya, a Cesium Certified Developer, uses CesiumJS to power its intuitive platform for 3D data visualization and analysis across organizations in government and education.

Eukarya is focused on knowledge sharing and disaster prevention. Courtesy Re:Earth by Eukarya.

Eukarya's Re:Earth uses CesiumJS to enable data visualization and collaboration, especially for those not well versed in working directly with the data.

Re:Earth by Eukarya

Re:Earth, a WebGIS platform requiring limited coding, was released in 2021 by Eukarya, a Tokyo-based group that began in the lab of longtime Cesium community member Dr. Hidenori Watanabe; the group is focused on knowledge sharing and disaster prevention. Eukarya sees Re:Earth as a digital public good, an open resource that uses the internet to benefit society. Re:Earth enables data visualization and collaboration, especially for those not well versed in working directly with the data. Users include Princeton University and the Japanese Ministry of Land, Infrastructure, Transport, and Tourism (MLIT)’s Project PLATEAU.

Tsunami simulation in Salinas, Ecuador, in Re:Earth. Courtesy Re:Earth by Eukarya.

MLIT’s PLATEAU, an application built on Re:Earth, is a digital initiative promoted by Japan’s national government to get open data 3D models of cities across Japan into a platform accessible to all levels of government. PLATEAU enables infrastructure assessment and urban planning, disaster preparedness and response, and environmental management. Geospatial tools and expertise can be lacking at local levels, so user-friendly administration and customization on the web without needing to code are vital for this app. Because PLATEAU’s Re:Earth base runs on CesiumJS, it can be accessed in a browser on any device with an internet connection, and large interactive datasets can be shared with just a link. Datasets added from any user are located on a high-precision WGS84 globe, ensuring consistency and accuracy. 

Re:Earth supports various data formats, like CSV, GeoJSON, CZML, KML, glTF, OBJ, and FBX. Users add their datasets to Cesium ion, where they are stored and tiled into 3D Tiles and streamed to CesiumJS to make visualization and sharing easy. Re:Earth also accesses Cesium World Terrain and Bing Maps Aerial imagery in Cesium ion.

MLIT PLATEAU'S Re:Earth base runs on CesiumJS. Shown here is the area around Tokyo Station in Chiyoda, Tokyo, Japan. Courtesy Re:Earth by Eukarya.

Eukarya plans to partner with more customers to aid disaster prevention and response with 3D visualization via Re:Earth. The company was recently a sponsor of FOSS4G 2023 in Prizren, Kosovo, to support open data for governments and educational organizations across the globe. Cesium will be at FOSS4G NA in Baltimore in October.

To learn to use CesiumJS and 3D data to move your GIS apps forward, follow our tutorials.

Re:Earth Uses CesiumJS to Bring Intuitive Data Visualization to Government and Education

Oceanites has been visiting Antarctica and counting penguins for 30 years, sharing the reality of climate change through the lens of penguin population dynamics. Oceanites uses Cesium Stories to get research into the hands of policymakers and the public more easily and in an interactive way. 

Drone photo of Oceanites researchers at Neko Harbour, Antarctica, monitoring a Gentoo penguin colony. Courtesy Oceanites.

Oceanites’ mission is to conduct and evaluate research on Antarctic penguin populations in support of climate science and inspire key stakeholders to act. During the Austral summer of 2022-23, Oceanites carried out drone surveys around the Antarctic Peninsula, including the Tetrad Islands and D’Hainaut Island, off Trinity Island, which is on the northwest side of the Antarctic Peninsula. 

This was Oceanites’ first season flying DJI Mavic drones to count penguins using photogrammetry. Penguins and their chicks are visible in 3D models created from the drone imagery. The organization aims to create a long-term 3D dataset of penguin colonies, to show population change over time due to shifts in snow cover at the colonies. The dataset will also serve as a record easily shared with colleagues, citizens, and policymakers.

Cesium Stories complement thorough research with interactive, geospatially accurate scenes without the need to write any code. Oceanites puts its data into context and augments slides with informative text and high-res images. By default, Cesium Stories include Cesium World Terrain, Bing Maps Aerial imagery, and Cesium OSM Buildings—while Oceanites didn’t need models of buildings on the Antarctic Peninsula, the other global layers provide context for the locations of penguin colonies. Oceanites’ 3D models uploaded to Cesium ion were tiled to 3D Tiles for streaming in these presentations.

In observing and sharing penguins’ ability to adapt—or not—to climate change in the Antarctic, Oceanites urges action to benefit not only the flightless birds but also humankind.   

To bring interactivity and global 3D data to your research presentations with no need to code, follow our tutorial to create and share your own Cesium Stories.

As climate change spurs more frequent, violent weather, accurate weather forecasts are becoming increasingly critical. WindBorne Systems is working to collect the data that no one else can reach. Their balloons fly hundreds of times longer than traditional weather balloons, and they visualize those flights in CesiumJS. 

A WindBorne Systems flight, visualized in CesiumJS.

To this day, weather prediction relies on data from balloons. Nearly half a million are launched every year, each carrying sensors to measure temperature, humidity, and pressure. These balloons fly for about 2 hours until they get too high and burst. 

WindBorne Global Sounding Balloon in the air over the Svalbard Islands, Norway. Courtesy of WindBorne Systems. 

WindBorne Systems has invented a new system to collect this data. Dynamic controls on their balloons allow them to adjust altitude in real time, releasing gas when a balloon gets too high and dropping ballast when it gets too low. Unlike traditional weather balloons, which burst 2 hours into flight, WindBorne balloons can stay aloft for more than 400 hours.

Here’s one balloon’s path in the Arctic, visualized in CesiumJS. WindBorne Systems has exaggerated the height 100x to make it easier to see. 

Over that time, a balloon may travel significant distances, both vertically and horizontally. In March 2022, one of their balloons circumnavigated the globe. During that flight, it successfully flew over the Alps and Himalayas, and also maneuvered to avoid Russian and Ukrainian airspace.

This 3D visualization of a flight of Balloon W-273, which circumnavigated the globe, shows the altitude adjustments as well as the balloon’s drift in its flight. 

Despite flying without an engine, these balloons can have remarkable control over their flight paths, just by adjusting altitude. In fact, by adjusting a balloon’s altitude to fly in wind currents moving in a desired direction, WindBorne Systems is able to steer their balloons. The 3D nature of these flights makes CesiumJS the ideal visualization tool for tracking a balloon’s path. 

By making multiple ascents and descents, WindBorne Systems is able to collect a more complete picture of atmospheric conditions. 

Capturing these flights in 2D would offer very little insight, since altitude is just as important as latitude and longitude. The 3D view available in Cesium, however, provides the whole picture. CesiumJS was built for accuracy at global scale, from the WGS 84 ellipsoid to terrain to the atmosphere and sun position. That full picture of Earth's surface and atmosphere supports true 3D visualizations.  

In early 2022, WindBorne Systems measured the formation of atmospheric rivers over the Pacific Ocean, systems which bring rain to the West Coast. That campaign included 65 balloons that collected data over more than 11,500 vertical km of profiles, and more than 675,000 km of ground track. 

These balloons face extreme conditions: vicious lightning, high winds, and temperatures down to -80°C. 

WindBorne’s 362nd Global Sounding Balloon on the ground, shortly before release. Courtesy of WindBorne Systems.

Last month, WindBorne Systems even sent a balloon into Hurricane Ian. With zero risk to human pilots, the balloons have a huge advantage over the manned aircraft that typically take measurements of hurricanes. 

The flight path of a WindBorne Systems balloon in Hurricane Ian. Providing insights into dangerous storms like these will allow forecasters to provide more specific, reliable guidance to the public. 

WindBorne Systems’ balloons provide access to areas like the Arctic and open ocean that are highly affected by climate change but are currently poorly observed. And providing better data about wind and other conditions will help protect lives and property against wildfires, cyclones, and other extreme weather. 

To visualize your own data in Cesium, get started with a free Cesium ion account. 

Measuring Weather with WindBorne Systems and CesiumJS

The Urban Data Project, developed by the GATE Institute at Sofia University, is tracking air quality data in Sofia with a CesiumJS application. 

The Urban Data Project includes a 3D model of the city of Sofia. 

The Urban Data Project supports better air quality monitoring and environment-aware urban planning. With Cesium, they’ve been able to integrate static models of the urban infrastructure with dynamic information from the environment.

The application provides data on air pollution from various sensor stations throughout the city. 

Air quality sensors throughout the city have been in place for some time, but that data has been fragmented in various applications. The Urban Data Project migrated these various applications to GATE’s platform for data processing on their private cloud. That migration required integrating information from multiple sources, including sensors, databases, and interactive models, which was all in different formats, e.g., JSON, SQL, KML, RDF. Those datasets were also ingested in different modes of delivery, including streaming, messaging, file uploads, database imports), and stored in different repositories, e.g., SQL databases, NoSQL databases, GML databases, graph databases, distributed file systems. 

Users can get more detailed information from each sensor, updated in real time. 

By integrating all the data and providing a simple, intuitive user interface built on CesiumJS, the GATE Institute made the data more accessible and simplified navigation so users can quickly find relevant data around buildings, streets, and transport routes. 

To get started building your own application, sign up for a Cesium ion account. 

Sofia University Synthesizing Air Quality Data with Cesium 

Today the International Atomic Energy Agency (IAEA) is launching a major update to their marine radioactivity portal—now built on Cesium—to give researchers better access to radiation data on man-made and naturally occurring radionuclides in the world’s oceans.

Scientists around the world, from any of the IAEA’s 172 member states, can use the IAEA’s Marine Radioactivity Information System (MARIS), which provides access to a comprehensive library of samples taken over the last 60 years and covering more than 100 different radionuclides found in the ocean.

Researchers are able to find relevant data using an interactive 3D globe built with Cesium. Scientists can filter by various parameters such as type of radionuclide, depth, or sampling date; can draw a polygon on the globe to cover the area they’re interested in; and can download results for that geographical area.

Previous versions of MARIS used 2D maps that could not support all the capabilities the IAEA was looking for. Because these maps used Web Mercator projection, they show significant distortion at high latitudes, which created a serious problem for studying polar regions.

The new Cesium application offers better navigation and search functions, making it easier for researchers to get the data they need. Many scientists using MARIS are looking for baseline data for a given area. By evaluating the naturally occurring radionuclides, and those released from industrial facilities, they can better assess trends in local areas, evaluate proposed industrial projects, validate marine models used for simulation, and understand the impact of both natural processes and human activity on the world’s oceans.

Sign up for a Cesium ion account to bring your own marine data onto a Cesium globe.

IAEA Tracking Radioactivity in Seawater in Cesium

The Map of Nottingham Energy Performance Certificates (EPC) uses 3D Tiles and Cesium to visualize the energy efficiency of buildings in Nottingham.

EPCs are a rating scheme used across the European Union for describing the energy efficiency of buildings. EPCs describe current and potential energy use, and they list recommendations that can be made to a property to improve the building’s efficiency. In the UK, residential properties are commonly assessed following their construction, during a sale or when renting them out, leading to a substantial and useful dataset of general and localized building energy use statistics. The register of EPC records and recommendations for England and Wales has been recently released as an open dataset.

To map this data, Julian Rosser of the University of Nottingham matched EPC addresses to Unique Property Reference Numbers (UPRN) by GeoPlace, which provides a link to the national identifier used for properties in the UK. This UPRN was then linked to the topographic identifier (TOID) of the Ordnance Survey building footprint and height. In cases where multiple EPC records were found for one property, the most recent survey result is taken.

Users can explore the city by address and filter buildings by current and potential EPC ratings.

An Interactive City Model Visualizing Energy Performance Data for Houses in Nottingham, UK

This is a guest post by Rayman Ng about his open source wind map built on top of CesiumJS.

Wind is an important element in studying the weather and climate, and it affects our daily lives in various ways. Analyzing wind is critical in many fields such as climate analysis and wind farm management. Visualizing it is crucial in being able to quickly understand the numerical wind data collected by measurement devices.

There are already some wind visualization applications, like Earth Nullschool and Windy, but unfortunately it seems that none of them can display the terrain, which is important for estimating the effect of wind on a specific location.

Cesium makes it easy to visualize dynamic wind data with Cesium World Terrain.

windy_terrain.mp4

Given that I could not find an existing visualization application that met all my requirements, I decided to make my own. I found Cesium, which contains almost everything I need: 3D globe and terrain, Web Map Service layer display, and a powerful rendering engine. Basically I just needed to implement the wind visualization part.

You can run the live demo in your browser or access the source code on GitHub.

Dynamic wind overlaid on WMS layer of wind speed.

A common technique to visualize wind is to use a particle system, which places lots of particles in the wind field and updates their positions regularly with the wind force. The trails of moving particles can be used to reveal the flow pattern of the wind.

Computing this many particles is possible using the GPU, since this is otherwise too slow to render in real time.

wind_on_atmosphere.mp4

At first I tried the Entity API to draw the particle trails, but the performance was not satisfying when I placed more than 10,000 particles. After some investigation, I realized that the Entity API performs computation on the CPU, and the computation for more than 10,000 particles is just too much for my CPU. For better performance, I needed to move the computation to the GPU, but I still had to render the trails, which meant working with the low level Cesium Renderer module.

In Cesium, the key object of the rendering procedure is `Cesium.DrawCommand`: it is created in `Cesium.Primitive`, dispatched by `Cesium.Scene`, and executed in the render engine. The `Cesium.DrawCommand` contains everything needed in rendering, for example, `Cesium.Framebuffer`, `Cesium.Texture`, and `Cesium.ShaderProgram`.

To perform custom rendering, a custom `DrawCommand` is required. To build a `DrawCommand`, first initialize its components, which are `ShaderProgram`, `Texture`, `Uniforms`, and `Framebuffer`, piece by piece, and then combine them together to create a `DrawCommand` object. To inject the `DrawCommand` into the render engine, a custom primitive object is needed. It does not need to implement all the methods of `Cesium.Primitive`, only the update, `isDestroyed`, and the destroy method are necessary. The update method will be called before the start of each rendering.

As for the computation on GPU (also known as GPGPU), by using the technique of rendering to texture, it is similar to doing custom rendering; just use a fullscreen quad as vertex shader and write the calculation code in the fragment shader. Fortunately, Cesium already provides the rendering to texture function—all I needed to do was simply pass my fragment shader code to `Cesium.ComputeCommand` and use `Cesium.ComputeEngine` to perform the GPGPU.

The final step is to add the `CustomPrimitive` that contains the custom `DrawCommand` to the `PrimitiveCollection` of `Scene`. Below is a fully commented example of how to create a primitive and add it to the scene with a custom draw command.

```
class CustomPrimitive {
    constructor() {

        // most of the APIs in the renderer module are private,
        // so you may want to read the source code of Cesium to figure out how to initialize the below components,
        // or you can take my wind visualization code as a example (https://github.com/RaymanNg/3D-Wind-Field)
        var vertexArray = new Cesium.VertexArray(parameters);
        var primitiveType = Cesium.PrimitiveType.TRIANGLES // you can set it to other values
        var uniformMap = {
            uniformName: function() {
                // return the value corresponding to the name in the function
                // value can be a number, Cesium Cartesian vector, or Cesium.Texture
            }
        }
        var modelMatrix = new Cesium.Matrix4(parameters);
        var shaderProgram = new Cesium.ShaderProgram(parameters);
        var framebuffer = new Cesium.Framebuffer(parameters);
        var renderState = new Cesium.RenderState(parameters);
        var pass = Cesium.Pass.OPAQUE // if you want the command to be executed in other pass, set it to corresponding value


        this.commandToExecute = new Cesium.DrawCommand({
            owner: this,
            vertexArray: vertexArray,
            primitiveType: primitiveType,
            uniformMap: uniformMap,
            modelMatrix: modelMatrix,
            shaderProgram: shaderProgram,
            framebuffer: framebuffer,
            renderState: renderState,
            pass: pass
        });
    }

    update(frameState) {
        // if (!this.show) return;
        // if you do not want to show the CustomPrimitive, use return statement to bypass the update

        frameState.commandList.push(this.commandToExecute);
    }

    isDestroyed() {
        // return true or false to indicate whether the CustomPrimitive is destroyed
    }

    destroy() {
        // this method will be called when the CustomPrimitive is no longer used
    }
}

// To begin the custom rendering, add the CustomPrimitive to the Scene
var viewer = new Cesium.Viewer('cesiumContainer');
var customPrimitive = new CustomPrimitive();
viewer.scene.primitives.add(customPrimitive);
```

Compared with the Entity API, the Primitive API with custom draw commands provides lower level functions, making it possible to achieve better performance but requiring more coding work. By making use of the powerful render engine, wind visualization is possible with satisfying performance, and I believe that there are many other ways to use this powerful yet general render engine.

For example, it was very useful to be able to switch between different imagery layers, so you can see dynamic wind data in its global context and easily switch to comparing it with historic wind data. This is shown below using the slider.

I spent several weeks on coding this demo. It would have definitely taken longer without the help of:

Kind experts in the Cesium Forum, especially Omar Shehata, a member of Cesium team.

The author of the Cesium custom primitive tutorial on GitHub, which provides code examples for custom rendering in Cesium.

GPU Powered Wind Visualization With Cesium

The Smithsonian Institution’s Eruptions, Earthquakes & Emissions (E3) app is a time-lapse animation of volcanic eruptions, earthquakes, and sulfur dioxide emissions from volcanoes for the last fifty years.

A precursor to E3 was on display in the Smithsonian’s Geology, Gems, and Minerals Hall. In an effort to make the application more widely available, Axis Maps developed E3 using Cesium for both 2D and 3D views. With Cesium, they were able to efficiently render and animate millions of data points in an interactive map. Each point is interactive: users can learn more about the event or visit external pages with even more information.

The app combines eruption data come from the Volcanoes of the World (VOTW) database maintained by the Smithsonian’s Global Volcanism Program (GVP); earthquake data from the United States Geological Survey (USGS) Earthquake Catalog; and SO2 emissions data from NASA’s Multi-Satellite Volcanic Sulfur Dioxide L4 Long-Term Global Database. The earthquake and eruptions data go back to 1960; the SO2 data go back to 1978, when such information began to be monitored. The app remains current by checking for updates weekly.

It uses BillboardCollections for the volcano animations, PointPrimitiveCollections for the earthquake animations, and PrimitiveCollections for the SO2 cloud animations.

The map is still on display in the Smithonian’s Museum of Natural History and is available anywhere through a web portal. E3 was a finalist for a Webby Award. It was also featured in the Smithsonian Magazine and by the BBC.

Learn about Eruptions, Earthquakes & Emissions with this Animated Smithsonian App

Hundreds of kilometers above Earth, precipitation satellites fly by, observing clouds and rainfall using passive and active sensors. Some of them measure the temperature of the atmosphere and surface, from which information can be gleaned about how much rain and snow are falling at that moment. Others bounce microwaves off the clouds, assessing what size water droplets and snowflakes are falling based on how those microwaves come back.

Global Precipitation Mission (GPM) satellite data is crucial to weather decision making and historical precipitation climatological analysis. GPM is a collaborative effort between the United States’ National Aeronautic and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). It has two primary instruments: the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI). DPR provides 3D scans of snow and liquid water above the Earth’s surface. GMI observes the brightness temperature of microwave radiation coming from Earth at numerous different frequencies. Both instruments combine to provide a thorough assessment of precipitation rates and types as the satellite orbits Earth once every 90 minutes between 65 N and 65 S latitude. GPM data are made available at the NASA STORM website anywhere from 24 to 36 hours after the original satellite flyover, while near real-time (NRT) data is output within 30 minutes for GPM microwave imagery (GMI) and 2 hours for dual-frequency precipitation radar (DPR).

Matt Lammers, web analyst/developer for the NASA Precipitation Processing System (PPS), has developed a number of systems to visualize this data in 3D using Cesium.

The STORM Virtual Globe allows users to explore global precipitation in 3D. The data is read directly from the raw HDF5 files, converted into JSON, and visualized in Cesium without storing any post-processed files. This is enabled by the STORM website being built on top of the Java Tomcat service, which allows the creation of servlets written in compiled Java to be exposed online. STORM VG performs Ajax queries to grab the satellite data from the servlet.

Depending on the file being explored, STORM VG presents the user with two different ways of exploring the precipitation rate information. Level 3 precipitation data (meaning it is stored in a non-orbit-based way) simply displays the entire grid at once. Each grid point can be moused over for the raw integer precipitation rate value. Level 3 GPROF files feature 0.25 degree gridded precipitation rate data from a single satellite aggregated over an entire day. Level 3 IMERG files combine information from a number of satellites with surface observations on a half-hour basis. Level 2 data (stored in an orbit-based way), being often higher resolution, is made available fifteen minutes at a time. Using a scroll element, the user can look at any portion of the orbit, with both camera motion and a polygon making apparent where the new segment will appear.

Radar products (2ADPR and 2BCMB) provide information both in the horizontal and the vertical about precipitation rate, and so data points are visualized both on the surface and through the lower atmosphere, giving information about the overall structure of storms. To see what’s possible with the Storm Virtual Globe, check out this perfect flyover by the GPM core satellite of the eye of Super Typhoon Vongfong in October 2014.

For outreach purposes, PPS highlights specific high-impact events in the STORM Event Viewer. The tool is updated frequently when GPM flies over new major events such as tropical cyclones and outbreaks of tornadoes.

STORM Event Viewer generates simple JSON files server-side on the fly from HDF5 binary files. These JSON files provide latitude, longitude, elevation, and precipitation rate values from which CesiumJS can then generate pointPrimitive objects. Because some of these events garner a lot of attention, JSON files are sometimes generated and stored ahead of time to minimize server impact and prevent latency.

To broaden the appeal of STORM Event Viewer, PPS adapted the interface to make it more friendly for mobile/tablet users and to enable its embedding in NASA news releases and articles. EVMini is stripped down for smaller screens, although it maintains the ability for users to view individual data point values and to read brief summaries of the events for context. It runs smoothly despite all of the points being displayed because CesiumJS is so mobile-friendly. EVMicro is designed to be embedded, so it removes all of the controls, preserving a simple interactive visualization that highlights the satellite data and the ability to delineate between frozen and liquid precipitation in the DPR scan.

Global Precipitation Mission (GPM) Near Real-Time (NRT) Viewer

GPMNRTView visualizes NRT data collected by GPM. The pipeline efficiently processes the GPM NRT HDF5 files into CZML and makes those files available for visualization for a rolling 12-hour period. Swath-based file sizes are kept small by tracking a cross-track set of pixels as they change through time rather than storing positions and visibility information for every pixel in the segment. This allows for further condensing of space by only tracking changes in color rather than storing each value for each instrument scan. Users must step through time to make data appear, but this can be sped up using the Cesium time widget controls.

Four products are available in GPMNRTView. Level 2A DPR is a narrow swath-based product that plots data points at storm top height, rather than on the surface, to provide a 3D representation of precipitation. Level 1C GMI is a wider swath-based product showing various brightness temperatures at various frequencies. Depending on the frequency, different atmospheric properties can be teased from the information, including wind speed and precipitation intensity. Level 2A GPROF takes the Level 1C GMI data and algorithmically converts it into precipitation information, such as probability of precipitation and precipitation rate.

The final product, Level 3 IMERG-Half Hour, takes information from several precipitation satellites along with model data and surface observations and generates precipitation rate information for a 0.1 × 0.1 degree latitude/longitude grid for a given half hour period with a latency of approximately 3 hours. With this data, not only is the entire globe shown at once (rather than information appearing for a swath as it animates), but also the data points can be moused-over to see the raw values.

While STORM Virtual Globe and GPM NRT show satellite data, STORM Virtual Globe HWRF (STORM VG HWRF) shows forecast data for Super Typhoon Nepartak, which struck the southeastern coast of Taiwan on July 7, 2016 with maximum sustained winds of 150 mph and a central pressure around 930 mb. 16 hours prior to landfall, the National Weather Service’s (NWS) Hurricane Weather Research and Forecasting (HWRF) model output projected radar reflectivities for the storm, anticipating the rainfall intensities that would be associated with Nepartak’s arrival. This output was stored in GRIB2 format (a World Meteorological Organization standard gridded binary format) and made available at the National Oceanic and Atmospheric Administration (NOAA) Operational Model Archive Distribution System (NOMADS) website.

It is important to recognize the interplay between observed values and computer model forecasts. Cesium has the ability to enhance the ways in which gridded atmospheric model output can be presented and investigated online. Despite advancements in high-resolution modeling of extreme weather events, it remains common to look at the model output with static 2D imagery. STORM VG HWRF shows that not only can 3D interactive visualization easily be done with this sort of data, but that it can be done online and shared among the entire scientific community.

Explore Precipitation Data On and Above the Globe with NASA STORM Virtual Globe

HOWL(Highlighting Oregon’s WildLands) is an interactive 3D/4D mapping and visualization tool for presenting information relevant to protecting wilderness and wildlife in Oregon. The application combines information from multiple data sources and presents it over 3D maps, and, when applicable, it provides the ability to animate the data presentation over time.

HOWL uses spotlights, introduced in the form of cards on the home page, to show information. Spotlights are mini-applications focused on specific topics or areas of interest. Currently HOWL has the following three spotlights available:

History of Wildfire Severity: Animation of wildfire events since 1984, with drilldown to individual fires and color-coded severity assessments.

Potential Wilderness Areas: Shows candidate areas for wilderness designation protection categorized by ecoregion.

The Journey of Wolf OR-7: Visualization and time animation of the migration route taken by the famous OR-7 wolf from northeastern Oregon all the way to California and back to Oregon’s Crater Lake area.

Spotlights are modules that can be added to HOWL. In the future, more spotlights will be added to focus on other areas related to wilderness protection. Some ideas under consideration include active wildfires, forest-based carbon storage, and additional wildlife tracking.

HOWL is built using Cesium and takes advantage of many of its features, including 3D data representation, time animation, CZML, terrain model, and imagery overlay layers. HOWL integrates additional open-source components such as ChartJS, JQuery, and BootsrapJS.

HOWL is a volunteer project made for Oregon Wild. The application is regularly updated with new features, and it is published as open source on GitHub. Contributions are welcome! Stay in touch by visiting the author’s blog.

Interactive Visualization for Protecting the Wilderness and Wildlife in Oregon

The Cesium team has been working with Planet to bring their imagery to the Cesium community. Planet images the entire Earth every day using their own satellites, developed in-house. With this imagery, they’ve built color-balanced, cloud-free whole earth base maps that range from seamless mosaics to automated mosaics produced at frequent intervals. Their time-sliced mosaics allow users to know exactly when each image was captured.

They’ve also created the Open California product, an openly licensed preview dataset of a California imagery archive with imagery as recent as two weeks after acquisition.

Cesium is integrating with Planet’s API to consume Planet’s imagery products, temporally. You can see a preview of this integration at GEOINT 2017. Get in touch and let us know your use case for time-dynamic satellite imagery.

An animation of a timeline demo we created with Planet's data. This shows a timelapse of the four seasons from Fall 2014 to Summer 2015 at San Luis Reservoir. Note the receding waterline showing the effects of California's most recent drought.


A slider bar in this demo allowed users to compare water levels in Winter 2014 and Summer 2015.


Planet's extensive archive of satellite imagery is well matched to Cesium's support for temporal data.

Users can adjust the timeline to see imagery at different times. These images of Mount Shasta were taken in 2013 and 2014. Note the clear shadows.