AI for edge computing in Earth Observation

With satellites increasingly generating data, AI-powered edge computing is set to change the game. Instead of sending everything back to Earth for processing, satellites equipped with onboard AI can analyze data in real time, reducing delays and enabling faster decision-making.

This means that industries relying on Earth Observation (EO), like environmental monitoring, agriculture, and disaster response, can get quicker, more actionable insights. To make this a reality highly-precise and reliable optical systems are key to ensuring accurate data interpretation.

The growing merger of defense and space goals

The lines between commercial space activities and defense applications are blurring, as securing space assets becomes just as critical as securing territories on Earth. This shift drives new collaborations and accelerates advancements in surveillance, secure communications, and threat detection technologies.

As defense strategies progressively rely on space-based assets, the demand for high-performance optical systems and precision imaging solutions is escalating. Expertise in space-based space situational awareness (SBSSA) is becoming extremely important.

Expand sensing capabilities with thermal infrared imagery

In several civilian and military applications, thermal infrared imaging is gaining momentum. By capturing temperature-based imaging, this technology plays a critical role in wildfire detection, infrastructure monitoring, and military reconnaissance.

As high-sensitivity thermal imaging advances, the need for specialized optical systems that deliver accuracy in extreme conditions—whether for night-time surveillance or environmental monitoring—continues to pose a key challenge.

Space debris tracking to safeguard the future of orbital operations

The surge in satellite launches has led to an increasing risk of space debris collisions. AI-driven monitoring and optical tracking systems are becoming essential to tackle this growing threat.

Protecting vital space assets requires precise debris-tracking capabilities. High-resolution optical payloads enhance real-time monitoring, helping both commercial satellite operators and government agencies maintain safer orbital paths.

Translate data into actionable strategies

Space-Comm 2025 made one thing clear: the future of space operations depends on advanced imaging, onboard AI, and robust space situational awareness.

At Lambda-X | Verhaert High-Tech, we collaborate with industry leaders to develop high-performance optical systems that meet their most demanding needs and standards. Our optics serve as key components to enhance real-time Earth Observation, strengthen defense applications, and improve space safety. By pushing the boundaries of optical engineering, we’re contributing to building a more secure, high-tech, and data-driven space ecosystem.

Ready to explore how optical innovation can advance your space projects? Let’s talk!

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Where it all began

In the past, public authorities have been the prime procurers and consumers of earth observation data and insights. However, as more companies have international markets and supply chains entangled in a global web of diverse environments, this EO data might fill in the gaps in your data sets and provide valuable insights for your management, planning, and reporting. Think of opportunities like detecting pollution or emission leaks, increasing biodiversity and growth in carbon sequestration projects (forests, fields), or improving the yields of low-income farmers.

What sparked the rise?

We’re currently in the next innovation wave with earth observation. Next wave? Yes, because the previous revolution in earth observation data was the commercialization of online GPS systems in the late 1990s. So let’s take a trip down memory lane:

Positioning

• In 1983, Reagan authorized the use of Navstar by civilian commercial airlines for positioning.
• By 1995, a new stronger version of Navstar, GPS was developed and fully operational.
• In the late 1990s, GPS increased its accuracy and became available for commercial use. In 2000, the GPS receiver and processing chips price dropped from roughly $3000 to $1.50. Both lead to exponential growth in GPS usage.

Earth observation

• Since the 1950s, authorities have been using earth observation satellites for spying and defense purposes.
• A first wave of commercial earth observation constellations came online in 2014. (Planet Labs, Blackbridge, Satellogic, Spire Global,…). Nevertheless, the majority of the customers remained governmental.
• Today, we see larger and larger constellations with more capable sensors being approved (400 000 approved in 2022, but not all are for EO) enabling more data, but also at lower price points.

In addition to becoming more easily available and cheaper, earth observation data is also providing more granular and detailed data with shorter time intervals. And this will only improve further as new constellations consist of smaller satellites and state-of-the-art cameras. Combining these inputs with data sets generated by connected thermometers, buoys, drone imagery, aerial photography and many more sensors, provide truly valuable insights in the changing conditions of environments, urban and industrial areas. Think of changing temperatures, unusual emissions of methane, carbon,…, departing ships and planes, tracking spills, and much more.

How can you get started?

The EO market is rapidly evolving, so even if you found drone imaging last year too expensive, a new player may have entered the scene with new solutions since then. So where do you get started sifting through the endless opportunities? FIRE, the non-profit industry-led Forum for Innovation and Research in European Earth Observation, aims to promote the adoption of EO solutions by shaping the research and innovation strategy for various industries.

From February 1st to 3rd, the FIRE Forum is dedicated to unlocking the benefits of EO in various industries, including agriculture, raw materials, urban development, infrastructure, wind energy, and marine & maritime. Dedicated teams will showcase and explore how aerial and drone footage can be replaced by satellites, as well as discuss the current capabilities and solutions available on the market.

Interested? Visit the FIRE website for more information and registration.
Curious to know more about how Verhaert supports EO application projects? Check out our capabilities and get in touch!

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Trends in NewSpace

What is going on that makes earth observation suddenly so accessible? In NewSpace we see that the satellites have become relatively small. Decreasing the material cost and the cost of bringing them into orbit.  This makes it easier for companies to have a presence in space. There has also been a shift from single expensive satellites to constellations of satellites. These consist of duplicates of a satellite that are spread across the globe to increase coverage and reduce costs. Think of a famous billionaire whose space company is doing just that.

In short, companies can now also acquire earth observation data. Aside from using data themselves, they also gain revenue by selling it. This trend of earth observation data being commercially available has truly made earth observation accessible to everyone. By paying a subscription fee, anyone could acquire a monthly quote of data. There even exist platforms where you can get earth observation for free! You are certainly familiar with Google Earth, one such provider of free earth observation data. As you can see, acquiring data has become quite easy. But what makes it so valuable?

What can I do with earth observation data?

The most important thing you can do with this data is to automate the generation of insights. It doesn’t matter if you are a shipping company managing a fleet, an energy company forecasting energy demands, or a farmer wanting a continuous overview of all your crops. You won’t be doing this manually. As the scale of these tasks has become so large, you need to automate this process as much as you can. This is where AI comes in.

As the world gets more globalized, and all our human endeavors scale, automating the generation of insights becomes mandatory in order to not fall behind.

A maritime shipping company might gain insights into how busy certain routes are, how the weather and sea are behaving, or what the ice formations in the arctic look like. A farmer could gain insights into the status of crops. Think not only of the health and readiness to harvest, but the yields as well. To give a few examples you might already have an idea for an application that will generate a lot of value for you. But first of all you will need data, and not just any data, you need the right data. What kind of sensors do you need? You have a lot of options to choose from, from selecting specific spectral bands to LiDAR and other types of sensors. For each of these, you can also determine their characteristics. Then you probably have some requirements for the resolution which can range from a couple of hundred meters per pixel to an incredible thirty centimeters per pixel. Another important requirement is the fly-over time, which determines how long it takes for a satellite to pass by the same location twice. And of course, we cannot forget that there is a cost to all this. Premium EO data can go from a few cents to over 50 euros per square kilometer.

Spring cleaning

Before you can start building applications, you need to do a bit of cleaning to make the data ready for use. Depending on the provider of your data this can be a lot of work or none at all. We distinguish three main steps that typically have to be taken. First is noise removal. Noise sources like stray light, smear and dark offset can automatically be dealt with by using specialized algorithms. Second is pixel labeling, meaning that for each pixel in every picture the location and timestamp need to be determined. Luckily, AI can help you in this early stage as well. There are plenty of algorithms available for this purpose.

The third step can be quite tricky. If you have selected multiple sensors to measure the same phenomena, you need to correct for inter-instrument bias. What do we mean by this? Each of these sensors should be measuring the exact same thing. However, slight differences might occur resulting in different values for the same phenomena. Incorrectly using this raw data could be disastrous for your project. It is of vital importance to correct this bias first! Fortunately, machine learning algorithms can be employed to this bias and correct it, even if we don’t fully understand where the bias is coming from.

Supervised vs. unsupervised model ©VERHAERT

Applications

Spring cleaning is done and the data is now ready to use. It’s time to actually build algorithms that can extract insights from the data. Typically, you would want to use a supervised learning algorithm for this kind of problem. But, that means we need examples to teach the algorithm what it should do. And I don’t just mean a few. A large dataset needs to be gathered and manually labeled in order to be able to build a good algorithm. You want to determine the air quality from spectral imaging? Well, then you need to make a lot of manual measurements first so the algorithm can learn from your examples.

Of course, this kind of approach is very expensive, so don’t we know a better way? Within the world of machine learning there also exists a group of unsupervised learning algorithms. These don’t need examples at all. One of the more interesting approaches to earth observation goes as follows:

1. 1. You select the sensors which should capture your problem quite well
   2. You apply a clustering algorithm with a high number of classes on this data. This algorithm can divide the world into similar parts based on this data.
   3. Finally, it’s up to a domain expert to give meaning to these classes.

Let’s go back to the air quality example. If the right information is contained in the data, the clustering algorithm will divide the world into parts with similar air quality. It is then up to a domain expert to give meaning to these classes in order to make the algorithm usable. Measurements still need to be made, but far less than before. The result is an approach that is much cheaper both in time and resources.

Conclusion

Leveraging AI techniques enables us to automatically generate insights from the vast amount of earth observation data that is at our disposal. In these times of rapid globalization, this is a must as we just can’t keep up performing these tasks manually. If you want to generate insights from the vast amount of earth observation data that is at your disposal. And even if you want to generate these insights manually, you can benefit from AI to clean up your data.  No matter how you look at it, AI has become critical in any earth observation project we can imagine. Applying it unlocks a whole new area of opportunities.

Want to learn more about AI in data observation? Take a look at this webinar session!

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Earth observation systems generate huge amounts of data. This is a blessing, but without large scale automated data processing and analysis can quickly become a curse for your project. In this talk, Niels Verleysen and Daniel Gheorghita, Consultants AILab at Verhaert explore the unique role that data science, machine learning and artificial intelligence play in making NewSpace data actionable.

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Accurate and precise data is extremely important when using remote sensing in your decision-making process. In this webinar, Pieter Deleye, Manager Innovation Acceleration Services – Strategic Innovation at Verhaert, and Stefan Adriaensen, researcher at VITO, share their knowledge built over several years about monitoring and calibrating optical payload of satellites in orbit as a service. This service allows them to further improve and preserve the quality of EO data products and its applications.

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The NewSpace ecosystem is booming thanks to the emergence of small platforms. Any company in earth observation is now more than ever able to launch satellite constellations and commercialize the data. However, developing micro- and nanosatellites is not without its challenges. In this session, Didier Beghuin, CTO Development, and Philippe Antoine, CTO Research, from Lambda-X share their insights on maintaining imaging quality, differentiating from competition and reducing costs and time in development.

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One of the biggest bottlenecks in EO applications remains revisit frequency. Especially in the agriculture and food industry, the current 5 days frequency means a tremendous loss of data. In this webinar, Benoit Deper, CEO at Aerospacelab shows how their MultiSpectral Companion Mission is set to overcome this obstacle and enable daily visits. Thanks to a set of small multispectral satellites, they will be able to generate recurring high-quality data, and many benefits and opportunities for several industries.

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The CASSINI Hackathons and Mentoring, initiated by the European Union and its space program, is a series of 6 hackathons that tackle global challenges using European space technologies. Now in its 3rd edition, this hackathon provides access to European space data, information and signals from Copernicus, Galileo and EGNOS, plus other valuable tools to help participants take on one of our three pressing challenges. The top ideas will be awarded at both local and EU levels, and the overall winners will enter a 6-month mentoring program that includes 100 hours of customized expert mentoring.

Here’s what to expect

If you’re a rising innovator in Europe, you’re invited to participate in the CASSINI Hackathon at one of our 10 locations. Each hackathon location features its own unique set of experts, prizes, and additional special features. Once you select a location, it’s time for registration, team formation and ideation! Your team will choose to solve one of three challenges, all related to the theme of European tourism:

1. Creating sustainable destinations: Develop innovative ideas or design new products or services that reduce the carbon footprint of tourism travel. For this challenge, participants are encouraged to explore the areas of carbon footprint measurement, alternative destinations or modes of transport, online travel agents and other intermediaries, disruptive travel concepts, and understanding travel patterns between cities or countries.
2. Experiencing lesser-known cities and cultures: Develop innovative ideas or design new products or services to offer travelers a unique and sustainable way to experience local destinations while supporting local businesses and communities. For this challenge, participants are encouraged to explore the areas of crowd management and slow tourism, personal recommendations and itineraries, social recognition and social media, state-of-the-art virtual travel experiences, and supporting local businesses and communities.
3. Exploring nature with care: Develop innovative ideas or design new products or services to offer tourists a unique and sustainable opportunity to explore our nature. For this challenge, participants are encouraged to explore the areas of conservation of local nature and biodiversity, social recognition, and social media, supporting local businesses and communities, the generation of (new) routes and points of interest, and tourist information about the environmental state of areas.

Get your spot

Remember, no previous space experience is required! This is your chance to engage with the sector, even if it’s for the first time. The application process couldn’t be easier: simply choose a challenge and decide how you’ll leverage EU space technologies to reshape European tourism. Register here: hackathons.cassini.eu

Hackers aren’t the only ones who can take advantage of the CASSINI Hackathons & Mentoring. If you’d like to participate as an organizer or mentor, we’d love to hear from you. All interested individuals, organisations, companies, and institutions are invited to apply to support the next generation of space-based entrepreneurs. Information on how to get involved can be found here for mentors and organizers.

Now is your chance to become part of this exciting European initiative to promote EU Space technology and its many applications. Hack with a purpose and leverage EU space data, services, and signals to strengthen and transform the way Europe does tourism! More information: hackathons.cassini.eu

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Space technology is a great opportunity to innovate and create a competitive edge in commercial services and products. In this webinar, Pieter Deleye, Manager Innovation Acceleration Services – Strategic Innovation, explains how the ESA Space Solutions Belgium initiative supports the integration in IoT, connectivity and AI within ports, cities and logistics with funding, ecosystems and expert mentors.

Interested in attending our ReThinking NewSpace webinar on March 29th together with Lambda-X, VITO and Aerospacelab? Sign up on the event page!

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EO for reliable, detailed and up-to-date information

Innovating NewSpace starts with improving optics in micro- & nanosatellites, data processing through algorithms and embedded AI Particularly earth observation proves to be a versatile tool for reliable, detailed and up-to-date information on services on Earth.

Using satellite data allows you to see the bigger picture, derive clear connected patterns and supplement local infrastructure for prediction models. Earth observation opens the doors for future business application in several fields, from agriculture and marine, to urban planning and material management.

4 sessions, 4 earth observation challenges

Although earth observation systems have improved tremendously over the years, the challenges in providing cost-effective data, making micro- and nanosatellite optical systems more effective and integrating AI, are still to be solved. During this webinar we’ll tackle 4 recurring challenges in 4 sessions:

• 9h30 – Commercializing EO through daily global coverage (Aerospacelab)
• 10h00 – Optical design challenges for earth observation (Lambda-X)
• 10h30 – Preserving EO data quality through in orbit calibration (VITO)
• 11h00 – The critical role of AI in earth observation (Verhaert)

Discover new insights on sustaining successful EO-based products and services in this era of big data and IoT during the ReThinking NewSpace webinar. For more information about the sessions, please visit the event page.

Sign up for the webinar ‘ReThinking NewSpace’

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