While most people may think of ChatGPT or deep fake images when they hear “artificial intelligence”, AI methodologies are proving beneficial for a variety of applications, especially in data-heavy industries such as Earth observation. Using new government and commercial models, customers are able to remotely monitor large ship fleets, measure poverty at a granular level, and track natural disasters to provide rapid, targeted aid to people in need.

This NASA Landsat-8 image shows the wildfires that raged across Maui on Aug. 8, 2023. Government agencies and private companies are developing new AI tools to prioritize satellite image processing for natural disasters and other events where a rapid response is essential. [Credit: NASA Earth Observatory image by Lauren Dauphin]

Satellites in orbit are producing more data than ever before, and operators are turning to sophisticated processing techniques to enable faster and more meaningful analysis across a range of applications. For Earth observation (EO) satellites, especially those producing optical imagery, one tool is quickly becoming essential: artificial intelligence (AI).

On Aug. 3, NASA and IBM released the first open-source foundation model for satellite image analysis, hosted on the Hugging Face platform and trained on Harmonized Landsat Sentinel-2 (HLS) data. The release includes demo models trained to identify geographical features such as burn scars and flooding.

Rahul Ramachandran, project manager and senior research scientist at NASA emphasized the importance of foundation models to advancing geospatial analysis in a press release for the partnership. “AI foundation models for Earth observations present enormous potential to address intricate scientific problems and expedite the broader deployment of AI across diverse applications,” he said.

NASA and IBM’s foundation model isn’t the only AI milestone reached by the space industry in recent years, either. AI and space have long associations, ranging from satellite maneuvering and spacecraft telemetry to Mars-based robotic navigation and exoplanet analysis. As commercial EO satellite constellations grow and produce more images every day, companies are developing AI-based software to compile data and provide usable, easy-to-understand products to their end users.

The market for commercial EO data is growing as commercial and government customers — including national security agencies with their own high-resolution satellites — find benefits in the satellite constellations and analytical tools. Markets and Markets estimates that the geospatial analytics market (valued at $78.5 billion in 2023) could grow to $141.9 billion by 2028.

The Volume of Space Data Is Increasing Rapidly

The EO industry has come a long way from the early space race days of strapping cameras to suborbital rockets. Now, commercial and government satellites take millions of photos of the Earth every day from a variety of orbits.

The number of EO and remote sensing satellites orbiting Earth is growing alongside overall payload launch trends. According to Space Foundation analysis, 265 EO/RS satellites were deployed in 2022, almost 40% more than in 2021. Of these satellites, the majority (67%) were optical, producing high-resolution images of the Earth. A decade earlier, only 18 of 193 satellites deployed were for remote sensing or environmental monitoring.

However, with frequent, high-resolution imagery comes millions of large files that need to be transmitted to Earth and stored for analysis. NASA’s Earth science data archive held 72 petabytes (one petabyte is equivalent to 1 million gigabytes) of satellite imagery by the end of fiscal year 2022. That amount is expected to grow rapidly over the next few years as more EO satellite missions are launched. NASA projects the archive could reach 600 PB before the end of the decade. Europe’s Copernicus program had 34 petabytes in its data archive at the end of 2022 and is expected to grow to 80 PB in six years.

Because many EO companies utilize constellations of small satellites rather than one large one as many government missions do, those companies also produce massive amounts of data. Planet Lab’s constellation has photographed every location on Earth 1,300 times on average. Maxar Technologies, founded on Oct. 5, 2017, has more than 125 petabytes in its own data archive.

AI Brings Efficiency to Satellite Image Analysis

The AI field is so versatile that different techniques can be used throughout the lifecycle of satellite data analysis for increased speed and accessibility. Esri, the geographic information system (GIS) company behind the ArcGIS software family, identifies three key ways to apply AI to geospatial analysis: automate tasks and repeat them quickly at scale, look at past patterns to make predictions, and search for patterns hidden in large amounts of data.

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NASA and IBM’s foundation model is built to make the initial data cleaning step easier and more accurate so that researchers can focus on their actual analysis of the identified features. This AI model has demonstrated a 15% improvement over traditional models while only needing half the typical training dataset. For EO image datasets, which require manually identified features from which the model learns, the smaller training dataset requirement is a massive timesaver.

The European Space Agency’s Φ-lab, in collaboration with Oxford University and Trillium Technologies, utilized the RaVAEn machine learning (ML) model to speed up an even earlier part of the satellite data lifecycle, transmitting large files to ground stations on Earth. This model is hosted and trained directly on satellites, allowing them to detect changes in images of the same location and to prioritize the downlink of the anomalies that are deemed important.

On the commercial side, most EO companies develop proprietary software that utilizes AI to clean and present analysis-ready data to their customers. Maxar’s DeepCore Suite consists of more than 100 models that process satellite imagery and identify object types, helping users build training data and AI models.

Similar to the RaVÆn model, BlackSky’s Spectra AI software processes satellite imagery, detects changes and prioritizes analysis of important events such as natural disasters or military movements. However, instead of identifying events for the model to photograph, the BlackSky team taught the software to monitor events itself, according to Chief Innovation Officer Patrick O’Neil.

“Tasking is automated,” he said. “Our AI reads the world’s news, including hyper-local foreign language news sources all the way from the Associated Press and BBC. It identifies emerging events around the world and automatically tasks our satellites to take an image.”

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Wide Range of AI Applications in Space

One of the biggest advantages of foundation models for satellite imagery analysis is that they can be adjusted for different use cases. NASA and IBM’s model includes demo applications such as categorizing types of crops or mapping flooded areas at a higher resolution than the original satellite image. Because the model is open-source, researchers can train it on different types of data to identify features of interest.

One of the most recent demonstrations of the versatility and effectiveness of AI is Synthetaic’s use of existing software, which identified and traced the path of a Chinese balloon as it flew over the United States in February. Synthetaic, founded in 2019, created the Rapid Automatic Image Categorization (RAIC) tool to identify features from a single reference image instead of relying on a large training dataset. Paired with unlabeled Planet Labs satellite imagery, Synthetaic CEO Corey Jaskolski located the balloon in less than two minutes using RAIC and a rough RGB sketch.

Many recent improvements in satellite image analysis focus on accessibility. New AI tools and user interfaces are enabling a wider range of individuals — including social scientists and journalists who may not have specialized training in geospatial analysis — to gain insights from satellite data and share the results.

One particularly useful application for optical satellite imagery is measuring poverty at a granular level within regions of interest. These AI poverty models, like the one developed by Stanford University’s sustainability and artificial intelligence lab, typically combine high-resolution daytime imagery with nighttime light intensity data that can represent how developed a location is.

While using satellite data is promising for research applications where traditional data is difficult to predict or collect, there are concerns that not all research is adhering to the best practices that are being established in this emerging field. A review published in October 2022 examined 32 papers that utilized similar ML methods and found that many lacked at least one of the three main requirements for AI models: transparency, interpretability, and domain knowledge.

Expanding Commercial Geospatial Markets

In response to the growing demand for geospatial analysis, many EO satellite companies are making strategic partnerships with — or acquisitions of — AI software companies. After Synthetaic’s success using Planet Labs imagery, the companies announced a formal partnership in April.

Maxar Technologies partnered with Blackshark.ai in 2022 to combine satellite imagery with 3D modeling tools, and later that year, the company acquired Wovenware to further grow its AI and 3D capabilities.

One opportunity for the industry came on Aug. 7, when the Office of Space Commerce modified licenses for many commercial EO constellations, lifting restrictions that included image resolution limits for the companies. Without these restrictions, private companies can provide higher-quality analysis to their non-government customers and continue to expand use cases for AI satellite imagery analysis.

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Infosys a global leader in next-generation digital services and consulting, and Spirit AeroSystems the world’s largest first-tier aerostructures manufacturer inaugurated their dedicated center for aerospace engineering excellence in Richardson, Texas to nurture local talent to meet Spirit’s growing aerospace and defense engineering needs.

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The Center for Aerospace Engineering Excellence, located at 2400 N Glenville Dr Ste 150 in Richardson, will enable Infosys to work more closely with Spirit AeroSystems to develop cross-functional solutions to pressing business challenges in the aircraft development lifecycle. The Center will help Spirit AeroSystems to strategically expand and operate in proximity with their customers and suppliers for manufacturing and MRO operations. It will facilitate training, upskilling, and reskilling of talent in digital engineering technologies so that Spirit AeroSystems can scale and accelerate their aircraft programs to meet growing business demand, while mitigating risks, increasing speed to market, optimizing costs, boosting productivity, and crunching the learning curve.

Jasmeet Singh, EVP and Global Head of Manufacturing, Infosys, said, “We are thrilled to be expanding our services to Spirit AeroSystems by providing them with pioneering technology and dedicated talent to help them revitalize their core businesses. Setting up the Center for Aerospace Engineering Excellence, within our own digital innovation hub, allows us to co-locate, co-innovate and co-create alongside Spirit AeroSystems and build on our passion for creating the next generation of top U.S. engineering talent to drive Spirit’s business aspirations.”

Infosys is a trusted partner for Spirit AeroSystems, delivering engineering services for all its major aircraft programs for over 18 years. Spirit leverages Infosys’ advanced engineering platforms and solutions across its complete aircraft development lifecycle including concept, detail design, manufacturing, quality engineering, system integration, supply chain and maintenance, repair and overhaul services and cost optimization programs.

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Dr. Sean Black, Senior Vice President, Chief Technology Officer and Chief Engineer, Spirit AeroSystems, said, “The strategic collaboration with Infosys in Richardson, Texas, will leverage the talent pool in the North Texas region and create a dedicated center for aerospace engineering excellence to cover the complete aircraft development life cycle for both new derivatives and in-service aircraft.”

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“Workplace leaders are facing the greatest opportunity of our generation to positively disrupt the way we work”

For years, companies have wasted billions of dollars on grossly underutilized office space, because until now, they had no way of knowing how much space they need, how to reduce real estate footprint without disrupting performance, or how remaining offices should be designed to deliver an experience that’s worth the commute.

“Workplace leaders are facing the greatest opportunity of our generation to positively disrupt the way we work,” said Steve Vatidis, Executive Chairman, HubStar. “Yet figuring out which work patterns and places will deliver the best outcome across three dimensions – your people, your company and the planet – is complex. This transition – from relatively static workplace management to dynamic workplace management – demands flexible, connected approaches, datasets and automation. That’s why the HubStar platform exists and why HubStar Space is essential for delivering a high-performance hybrid workplace.”

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Legacy space management tools and approaches that served workplace leaders well up until now can no longer cope with the demands of today’s workforce. Why?

1. They lack the ability to assign people to spaces based on complex work patterns and preferences, making it impossible to execute an effective hybrid occupancy strategy
2. They are unable to update floor plans with the speed and accuracy hybrid strategies require, leading to frustration for employees relying on out-of-date office maps

As a result of these shortcomings, space planners face sky-rocketing costs as they attempt to create workarounds and custom code that render systems unsupported, error-prone and requiring untenable person-hours to maintain.

HubStar One – which brings together integrated solutions – HubStar Scheduling, HubStar Experience, HubStar Utilization and now HubStar Space – was built to solve these challenges, empowering workplace leaders to adopt an agile approach to managing continuous change.

HubStar is a privately held, global company with headquarters in Marlborough, Mass and London, UK. The company provides a next-generation hybrid working platform to drive productivity, collaboration and workplace experience while reducing real estate costs. With operations in the US, UK, Europe and APAC, HubStar helps thousands of teams in over 60 countries create dynamic workplaces across diverse industries

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Maxar Technologies, provider of comprehensive space solutions and secure, precise, geospatial intelligence, announced that the Galaxy 37/Horizons-4 satellite built for Intelsat is performing as expected after launch. The spacecraft was manufactured by Maxar in Palo Alto, California, and launched on a SpaceX Falcon 9 rocket from Cape Canaveral Space Force Station in Florida.

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“Our newest satellite for Intelsat adds to the capability that Maxar spacecraft deliver to people across the globe”

Shortly after liftoff and separation, the satellite began receiving and sending signals and deployed its solar arrays. After the spacecraft’s journey to its orbital position, two payloads will begin operations. Intelsat will use C-band capability over the continental United States, and the Ku-band will provide continuity over the Pacific Ocean and United States for mobility, network and government customers with a payload jointly owned by Intelsat and JSAT International.

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“Our newest satellite for Intelsat adds to the capability that Maxar spacecraft deliver to people across the globe,” said Chris Johnson, Maxar’s Senior Vice President and General Manager of Space. “Maxar built six geostationary spacecraft for Intelsat in three and a half years. That shows how fast and focused our employees are in delivering capability when our customers need it most.”

The Galaxy satellites Maxar built for Intelsat are based on the proven Maxar 1300™ platform, which offers the flexibility and power needed for dual-payload missions like this one. Galaxy 37/Horizons-4 joins four satellites built on this bus already in orbit that transition Intelsat’s broadband coverage to free up spectrum for 5G terrestrial wireless services.

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Intelsat, operator of one of the world’s largest integrated satellite and terrestrial network and leading provider of inflight connectivity, announced the successful launch of Galaxy 37/Horizons-4 (G-37/H-4), setting a new record for the commercial satellite industry by sending eight geostationary satellites into space within 10 months.

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“This milestone is now a part of the 40-year Galaxy legacy – satellites our North American customers have relied on for decades. It also marks the 20-year anniversary of our JSAT partnership. This joint venture has allowed both companies to serve more customers in more places throughout the world.”

“This launch completes our comprehensive Galaxy fleet refresh plan started about 10 months ago,” said Dave Wajsgras, CEO at Intelsat. “This milestone is now a part of the 40-year Galaxy legacy – satellites our North American customers have relied on for decades. It also marks the 20-year anniversary of our JSAT partnership. This joint venture has allowed both companies to serve more customers in more places throughout the world.”

The Maxar-manufactured satellite launched aboard SpaceX’s Falcon 9 rocket from Cape Canaveral Space Force Station in Florida at 1:00 a.m. EDT. G-37/H-4 separated from the vehicle at 1:33 a.m. EDT, and Intelsat confirmed its signal acquisition at 1:37 a.m. EDT.

When operations start later this year, G-37/H-4 will be positioned at 127 degrees West and deliver a wide range of services and coverage. The G-37 C-Band payload will provide North American capacity for television media and telecommunication network customers. The H-4 Ku-band payload will provide continuity for our mobility, network, and U.S. government customers and will be owned jointly by Intelsat and JSAT International, the U.S.-owned subsidiary of SKY Perfect JSAT Corp.

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Intelsat’s global team of professionals is focused on providing seamless and secure, satellite-based communications to government, NGO and commercial customers through the company’s next-generation worldwide network and managed services. Bridging the digital divide by operating one of the world’s largest and most advanced satellite fleet and connectivity infrastructures, Intelsat enables people and their tools to speak over oceans, see across continents and listen through the skies to communicate, cooperate and coexist. Since its founding six decades ago, the company has been synonymous with satellite-industry “firsts” in service to its customers and the planet. Leaning on a legacy of innovation and focusing on addressing a new generation of challenges Intelsat team members now have their sights on the “next firsts” in space as they disrupt the field and lead in the digital transformation of the industry.

SKY Perfect JSAT Corporation is Asia’s largest satellite operator with a fleet of 16 satellites, and Japan’s only provider of both Multi-channel Pay TV broadcasting and satellite communications services. SKY Perfect JSAT delivers a broad range of entertainment through the “SKY PerfecTV!” platform, the most extensive in Japan with a total of approximately 2.8 million subscribers. SKY Perfect JSAT’s satellite communications services, which cover Asia, Indian Ocean, Middle East, Pacific Ocean and North America, play a vital role in supporting communications infrastructures for mobile backhaul, government, aviation, maritime, oil & gas and disaster recovery.

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