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ESA InCubed and UKSA fund five Earth Observation projects

Posted on by mavelar

The joint ESA InCubed/UKSA funding call has awarded over £ 2.5 million to five projects that will turn Earth Observation data into essential public services. The funding supports projects tackling national priorities: CORE for safer infrastructure monitoring, GHGSat’s platform for tracking methane emissions, and three systems – THICKET, FANTOM and EO4Biodiversity – designed to support sustainable land management and enhance biodiversity.

The European Space Agency (ESA) and the UK Space Agency (UKSA) have announced the results of their joint InCubed funding call, awarding over £ 2.5 million to five innovative projects that use satellite data to improve public services.

This initiative is a clear example of how the ESA InCubed programme supports its member states’ governments in the development of a domestic space industry that serves public good. The call’s explicit requirement for proposals to target a public sector end-user shows that ESA is actively steering its investment towards applications that can directly benefit citizens and government operations.

After a very successful and fierce competition, here are the new five ESA InCubed/UKSA-funded projects:

CORE: satellite insights for infrastructure safety

Corner Reflector Enabled Remote sensing (CORE), developed by Geospatial Ventures Limited and Bloc Digital, is a solution for monitoring public infrastructure and ground stability.

Traditional surveying methods are often costly, slow, and pose a risk to personnel, especially when inspecting large building complexes or difficult-to-access terrain. CORE addresses these challenges by combining multiple satellite data streams – from Interferometric Synthetic Aperture Radar (InSAR) and high-resolution optical imagery – to detect small movements, providing a much clearer, more comprehensive view of conditions across urban and rural landscapes than single-source systems.

CORE will translate complex satellite data into actionable intelligence for public sector users, such as engineers, urban planners, and environmental managers. By integrating satellite data with artificial intelligence and machine learning, the system provides early warning of ground shifts, structural settlement, or degradation before issues escalate into dangerous or expensive failures.

“Through CORE, we’re demonstrating how Earth observation—InSAR and optical—can deliver valuable and practical benefits for stakeholders by providing early insights into environmental change, ground stability, and asset condition. ESA’s support through InCubed is essential in helping us accelerate development, integrate advanced EO capabilities, and transform satellite intelligence into actionable information that helps organisations manage risk, reduce maintenance costs, and strengthen environmental resilience,” stated Paul Bhatia, Managing Director at Geospatial Ventures Ltd.

THICKET: a biodiversity mapping tool to support sustainable agriculture

THICKET is a tool being developed by AAC Clyde Space to help farmers enhance sustainability and better support wildlife on their lands.

The system will use the upcoming VIREON constellation of satellites, which will capture frequent, high-resolution multispectral images – with a detailed 1.5-meter resolution – to map habitats across farmlands. This constellation was engineered to provide well-aligned Earth observation data, including spectral bands that align with Sentinel-2 bands, complementing existing initiatives like Copernicus.

By showing farmers what biodiversity assets they have, THICKET provides the data for them to make informed, sustainable farming decisions. This capability is crucial for supporting environmental management and directly helps farmers meet the requirements to access valuable government support programmes like the Sustainable Farming Incentive.

“The ESA InCubed/UKSA co-funding has been instrumental in accelerating the development of THICKET. By combining advanced satellite technology with AI, we are creating a scalable, cost-effective way to monitor biodiversity across farmland. With imagery from our upcoming VIREON constellation, we can now capture fine details like hedgerows and flower margins — features that were previously almost impossible to assess systematically. This collaboration is helping to make biodiversity visible, measurable and actionable, supporting both farmers and the UK’s broader sustainability goals,” commented Pamela Smith, Director of Government Programmes at AAC Clyde Space.

Government GHG Service: tracking methane for net-zero

GHGSat UK and Terrabotics are developing an advanced analytics platform, Emissions Watch Service, to convert satellite observations of greenhouse gases (GHGs) into practical, actionable insights for the government. This service is uniquely positioned to support the UK’s goals of reaching net-zero emissions by 2050. By using their proprietary constellation of satellites, GHGSat traces the source of GHG emissions directly to specific industrial facilities, with a focus on the powerful GHG methane.

The platform enriches raw satellite data with detailed industrial asset information, creating a robust tool for environment compliance and reporting. Its rapid detection capability will ensure accurate data is available within hours of an emission event, allowing the UK government to make informed decisions about targeted mitigation strategies and increase accountability across major emitting organisations.

“ESA InCubed is a powerful programme, harnessing the innovation of space-based technologies for government agencies in the UK and Europe. For GHGSat, the support from InCubed is critical in order to de-risk product development while leveraging ESA’s technical expertise, enabling us to develop a platform that is honed to solve the unique challenges that government faces,” commented Daniel Wicks, Managing Director at GHGSat UK.

“Ultimately, through InCubed, GHGSat will strengthen its analytics prowess, identifying and mapping sources of methane to create a comprehensive view of emissions to inform data-backed policy, strengthen regulatory compliance, and drive methane reduction,” Daniel added.

FANTOM: advanced environmental analytics for land management

FANTOM (Future Analytics for Nature Through Observation and Modelling) is a project from Earth-i and Specto Natura designed to transform environmental land monitoring across the UK. It builds a database of agricultural and biodiversity markers, creating novel environmental indicators directly from satellite imagery.

FANTOM’s scope will extend well beyond agricultural subsidies: the platform is designed to provide content and context that supports not only agricultural schemes but also net zero and broader climate change mitigation activities. The comprehensive database of markers and impact assessments will be made available to all governmental agencies, associated arms-length bodies and commercial companies, enabling them to monitor and measure the progress of their sustainability activities and interventions.

“Earth-i’s FANTOM project, supported by the InCubed programme, will build a high spatial and temporal resolution, UK-centric database of agricultural and biodiversity markers with rich information content,” comments Jennifer King, Project Manager at Earth-i. 

“This will support environmental schemes aligned with the UK’s Agricultural Transition and assist government policy implementations for Net Zero and biodiversity net gain. FANTOM will provide analytics directly to the Rural Payments Agency, which manages farming subsidies and environmental schemes for England. Following this, Earth-i aims to promote the service to other countries, tailoring the analytics products as necessary,” Jennifer added.

EO4Biodiversity: satellite tracking for habitat net gain

EO4Biodiversity is an innovative project led by HR Wallingford to leverage satellite data to improve plant and animal diversity. The project’s aim is to automate biodiversity impact assessments by developing new ways of using Earth observation data to track habitat changes over time.

EO4Biodiversity will streamline the assessment process for land development and environmental management by post-processing existing Earth observation datasets, such as the ones from ESA WorldCover, specifically for biodiversity evaluations. By automating complex assessments, this initiative moves beyond manual surveying, providing public entities and other stakeholders with a powerful and scalable service to inform planning decisions, ensure compliance, and strategically support the long-term sustainability of the UK’s natural environment.

“EO4Biodiversity is a UK-wide project that uses satellite data to improve how we measure the impact of infrastructure projects on nature. With support from InCubed, the team is developing a new tool that will help landowners, developers, and public organisations understand how different building plans affect local biodiversity. This will make it easier to protect and enhance natural habitats while meeting the UK government’s biodiversity net gain targets,” stated Marta Roca Collell, Principal Engineer, Flood and Water Management, HR Wallingford.

The campaign manager, Pejman Nejadi (End-to-end Systems Engineer at the ESA Φ-lab Invest Office), commented: “This campaign stands as a clear demonstration of the value that ESA’s InCubed programme can deliver in partnership with national agencies. By combining ESA’s unique technical expertise and programme management experience, with UKSA’s strong understanding of national priorities, we created an initiative that directly addressed the UK public sector’s need of Earth Observation data. The success of this campaign highlights both the strength of our collaboration and the effectiveness of InCubed in fostering solutions that bring real benefit to society.”

To know more: ESA InCubed, Geospatial Ventures Limited, Bloc Digital, AAC Clyde Space, GHGSat UK, Terrabotics, Earth-i, Specto Natura, HR Wallingford

Photo courtesy of Unsplash/Paul Fiedler

AI challenge advances satellite-based disaster mapping

Posted on by mavelar

Four teams from different countries have been recognised for their breakthrough work in using artificial intelligence to detect earthquake damage from space, marking the conclusion of a global competition organised by the European Space Agency in collaboration with the International Charter ‘Space and Major Disasters’ – commonly referred to as ‘the Charter’.

The winning teams – TelePIX from the Republic of Korea, Datalayer from Belgium, DisasterM3 from Japan and Thales Services Numériques from France – were honoured recently during a ceremony held at the Charter’s 54th Board Meeting in Strasbourg, as France’s French Space Agency, CNES, took leadership of the Charter for the next six months.

Combining the Charter’s operational experience with ESA Φ-lab’s drive for innovation, the ‘AI for Earthquake Response Challenge’, which is part of the ESA Φ-lab Challenges initiative, brought together 143 participants from 40 countries to explore how far artificial intelligence can go in automating post-disaster damage detection from space.

Read the full article on www.esa.int.

Photo courtesy of ESA Φ-lab Challenges.

The BiDS Award spotlights top European space start-ups

Posted on by mavelar

The BiDS Award, a joint initiative by ESA Φ-lab and ESA BIC Latvia, took place at the 2025 Big Data from Space (BiDS) conference to boost European space start-ups and academia. The award provided visibility and networking opportunities for those working on space-based solutions that address global challenges, facilitating the commercialisation of deep-tech innovations. The winners of the 2025 edition were AgroRisk, SALUTS, and Hyphorest.  

The BiDS Award, organised jointly by ESA Φ-lab and ESA BIC Latvia, took place on 2 October 2025, within the framework of the Big Data from Space (BiDS) conference. This award brought industry, research, and policy leaders together to explore how deep tech solutions and space data can be leveraged to address critical global challenges.

This initiative focused on transforming raw data into knowledge, insight, and foresight, showcasing how advancements on space technologies are boosting data usage to deliver impactful planetary solutions, and providing visibility and networking opportunities for European space start-ups and academia.

While proposals at the intersection of Earth observation and global challenges were central, the scope was broad, encouraging solutions from across the entire space value chain. This included upstream, downstream, and spin-in innovations such as advanced materials, robotics, quantum technologies, satellite communications, in-orbit services, navigation, and AI-driven analytics.

The award’s areas of focus included precision agriculture and food security, environmental sustainability and biodiversity tracking, or sustainable energy and infrastructure monitoring, among many more. The winners were awarded one year of free access to AI-data analytics platforms from Altair (in a total value of € 300.000) and access to satellite imagery from Airbus (valued in a total of € 25.000).

The third place was awarded to Hyphorest (Germany), a Stuttgart-based startup and incubatee of ESA BIC Baden-Württemberg that aims to bring finance to nature by making it easy to invest in restoration, carbon farming, and carbon removal projects that are measurable, transparent, and grounded. Using satellite data, AI, and blockchain, Hyphorest quantifies natural impact such as biomass, biodiversity, CO₂ storage, and ecosystem recovery, while strengthening the role of local and indigenous communities in achieving these goals.

The platform enables companies and individuals to invest in climate and nature-positive projects with measurable outcomes, turning environmental and social impact into a trusted, data-driven asset class. The solution presented at BiDS helps companies invest in nature, track their impact, and report results within their corporate sustainability targets and frameworks. Hyphorest’s mission is to build trust in nature-based investments and make real progress visible to everyone.

“Winning the BiDS Award affirms our belief that space technology is one of the most powerful tools for climate resilience. At Hyphorest, we turn satellite data into living evidence of restoration, making environmental impact measurable, transparent, and investable. Being recognised by ESA Φ-lab and the BiDS community encourages us to keep pushing the frontier where space innovation meets nature,” commented Hojjat Mansourpour, Founder and Chief Executive Officer of Hyphorest.

SALUTS (Germany) confirmed its position as a leading innovator in the European space-tech ecosystem by winning the second place. SALUTS’ mission is to redefine AI-driven autonomy in space and beyond by transforming space computing with ultra-efficient chips that enhance real-time, in-orbit data processing. Their vision was first recognized in 2023 when SALUTS won the 5th CASSINI Hackathon, an achievement that led to their selection by ESA BIC Bavaria to further develop their winning project.

The innovation that secured their BiDS Award recognition is CHIRB (Computing on Hybrid Interplanetary Relay Basis), a revolutionary advanced AI system that acts as the next-generation mission control centre for space, defence, and industrial AI applications. At the heart of CHIRB is Robot-on-a-Chip, SALUTS’ proprietary AI technology, whose chips are engineered to use 90% less power while providing three times more reliable data processing directly on the device.

CHIRB integrates seamlessly with existing infrastructure, featuring a natural language interface that lets any user simply chat their requests, which are converted by the system into working code and hardware control, thus eliminating the need for complex coding or technical knowledge.

“At SALUTS, ‘We Deliver Autonomy at the Edge and Clarity at Scale’. Our platform, CHIRB, combines ultra-low-power hardware modules with advanced AI software to make complex operations autonomous, efficient, and sustainable. The outcome: faster decisions, lower costs, and more reliable operations,” stated Mohamed Sobhy Fouda, Chief Executive Officer and Founder of SALUTS.

The first place was awarded to AgroRisk (Denmark), a climate fintech platform and incubatee of ESA BIC Denmark that quantifies agricultural and financial risks caused by climate change and extreme weather. By combining Earth observation data, weather models, and financial risk analytics, AgroRisk enables banks, insurers, and farmers to assess the climate exposure of agricultural assets at both field and portfolio level.

The platform translates satellite and climate data into actionable financial insights, helping financial institutions comply with new sustainability regulations and supporting farmers in adapting to a changing climate. AgroRisk contributes to food security, climate adaptation, and sustainable finance — leveraging space technology to enable data-driven resilience in the agricultural sector.

“Space data is transforming how we understand and manage climate risks on Earth. At AgroRisk, we use satellite-based insights to translate what happens in orbit into tangible value on the ground — helping banks, insurers, and farmers make smarter, more sustainable decisions. The BiDS Award highlights how space innovation can directly contribute to planetary resilience and sustainable finance,” commented Theodor Christensen, CEO and Founder of AgroRisk.

The winners of the 2025 BiDS Award. From left to right: Sabrina Ricci (AI Ecosystem Coordinator at ESA Φ-lab), Hojjat Mansourpour (CEO and Founder of Hyphorest, 3rd place), Mohamed Sobhy Fouda (CEO and Founder of SALUTS, 2nd place), Theodor Christensen (CEO and Founder of AgroRisk, 1st place), and José Manuel Delgado Blasco (Geospatial System Engineer at ESA Φ-lab). Photo courtesy of ESA/Sabrina Ricci.

A special recognition goes to Andrii Chepurnyi, PhD student at the University of Latvia, who received a prize for his Earth observation-calibration project. As part of the award, he will join the Commercialization Reactor’s Commercialization Dive programme.

Andrii Chepurnyi (middle), PhD student at the University of Latvia, won a special recognition. Photo courtesy of Gatis Orlickis.

“The BiDS Award is another example of collaboration between organisations dedicated to developing the European Space capabilities in Deep Space and Earth Observation. In this occasion, both industry and academia responded positively, as well as partners and sponsors needed to make this award a success. This success, along other parallel efforts, wants to push the limits of Space technology and help develop European champions that proposed solutions to real problems with space technology,” commented José Manuel Delgado Blasco, Geospatial System Engineer at ESA Φ-lab and co-organiser of the BiDS Award.

“In this award, we have collected many brilliant participants addressing problems such as space debris, environmental and atmospheric pollution, and climate change. It has been a pleasure to work with ESA BIC Latvia, Airbus and Altair and I want to thank all the people involved and participants who made this award a success – and a starting point for future collaborations,” José added.

“The success of the BiDS Awards within such a vibrant and diverse ecosystem as the Big Data from Space community confirms how rewarding it is to push the boundaries of space and connect with emerging pioneers of technology. Their contributions help us drive innovation both in Earth Observation and in Space. The enthusiastic response from sponsors, participating companies — including those who did not win — has encouraged us to continue promoting these initiatives as catalysts for new collaborations and interactions,” commented Sabrina Ricci, AI Ecosystem Coordinator at ESA Φ-lab and co-organiser of the BiDS Award.

To know more: BiDS Award, ESA Φ-lab, ESA BIC Latvia

Photo courtesy of Gatis Orlickis

Towards a ‘Mission Control for Earth’: Better understanding Earth’s systems using AI and space data

Posted on by mavelar

In August 2025, FDL Earth Systems Lab presented three big AI research outcomes to improve how we understand and predict Earth’s changing systems and offer a window on how we might build a ‘Mission Control for Earth’. Leveraging the European Space Agency’s missions and funded by ESA Φ-lab, this initiative combines fresh datasets with innovative AI tools to give the global community better ways to track and respond to our planet’s most urgent environmental shifts.

“Guided by artificial intelligence, driven by human good”. This could be FDL Earth Systems Lab (ESL)’s motto. ESL is a research collaboration framework funded by ESA Φ-lab and implemented by Trillium Technologies, with the support of University of Oxford, Google Cloud, NVIDIA, Scan AI, and Pasteur ISI. It focuses on artificial intelligence (AI) – in particular machine learning (ML) – to support Earth sciences, helping researchers create practical tools for some of humanity’s toughest challenges with the best of motivations: ‘planetary stewardship’. 

FDL Earth Systems Lab has run annually since 2008. Experts with deep knowledge of the challenge domain work side by side with data scientists to develop new AI-enhanced approaches and tools. The short, focused format encourages quick testing and refinement, ensuring stronger results.

Last August, the ESL 2025 Live Showcase featured three ambitious research sprints: (1) refining 3D cloud models to improve forecasts of extreme events; (2) testing how well foundation models perform in sparsely observed events; and (3) advancing onboard ML to spot short-lived atmospheric events, such as greenhouse gas emissions. Each sprint brought together unique datasets and new AI-based methods to support the global research community.

Photo courtesy of Trillium Technologies.

3D CLOUDS FOR CLIMATE EXTREMES

Advancing global 3D cloud reconstruction is essential to deepen our understanding of cloud structure and the interactions with terrestrial and atmospheric phenomena. This is critical for tropical cyclones, which remain among the hardest weather systems to predict, especially during the intensification stage. Forecasts often poorly resolve a cyclone’s internal dynamics, simulations of cloud properties are highly uncertain, and observational records are limited, with only about 80 to 90 tropical cyclones occurring each year. The ‘3D Clouds for Climate Extremes’ sprint builds on a mature model training pipeline established in ESL 2024, which successfully modelled 3D clouds from geostationary data.

First, the team pre-trained a sensor-independent model on a large dataset of top-view satellite imagery from GOES-16, MSG and Himawari-8, to reconstruct masked versions of the observations. Second, they fine-tuned the model using a dataset from CloudSat, which provides vertical cloud profiles. The team also created a benchmark dataset, by combining satellite imagery with the timing and location of cyclone events. Since the model is sensor-independent, it is possible to include other satellite data that were not used for training, ensuring global coverage.

Together, these data enable the reconstruction of key microphysical properties of clouds, including ice water content (notably elevated in rapidly intensifying cyclones), droplet effective radius (a critical factor in cloud absorption and reflection of sunlight), and radar reflectivity (linked to cloud density and an indicator of rainfall).

Improving the prediction of cloud structures in three dimensions opens opportunities for a wide range of scientific and applied use cases: forecasts of hurricane intensity, discriminative cloud classification, or to understand how deforestation influences cloud cover and type. This ambition aligns closely with the objectives of ESA’s cloud, aerosol and radiation explorer mission,EarthCARE, which aims to advance our understanding of cloud-aerosol-radiation interactions.

FOUNDATION MODELS IN EXTREME ENVIRONMENTS

Earth observation foundation models are very powerful tools, but they also have limitations, especially when facing unfamiliar scenarios such as extreme events. One of the reasons is that training datasets typically contain limited examples from these events, leading to weaker performances when applied outside the conditions represented in the data.

When queried about a particular topic, foundation models can be ‘confidently wrong’. This becomes especially problematic when these models are used in critical, time-sensitive situations such as disaster response. It is essential to increase model transparency in cases where the model output has a high degree of uncertainty and requires human validation. But how can we know if the model is uncertain? 

The ‘Foundation Models for Extreme Environments’ team brought a novel answer to that question. The team – mentored by Φ-lab’s Internal Research Fellows Patrick Ebel and Ruben Cartuyvels – focused on distinguishing two types of uncertainty: data-driven or model-driven.

SHRUG-FM (Systematic Handling of Real-world Uncertainty for Geospatial Foundation Models) was developed as an adaptable framework for the community that combines input and training image comparison, embedding comparison, and the foundation model’s output and uncertainty into a planning and selective prediction mechanism, to ensure that the model can give a prediction, raise a warning, or simply say that it does not know the answer.

STARCOP2.0: ATMOSPHERIC ANOMALY DETECTION FROM ONBOARD

One of the most urgent applications of Earth observation is detecting and tracking greenhouse gas (GHG) emissions that are driving global warming. Methane, in particular, is one of the most powerful heat-trapping gases. Hyperspectral satellites play a crucial role in the detection of such gases: each gas interacts with light in a unique way, creating a distinct ‘spectral signature’ or ‘fingerprint’ that allows its identification from space.

The STARCOP 2.0 solution is built on a ‘tip-and-cue’ system that makes use of hyperspectral satellite data. In this setup, the ‘tip’ satellite is responsible for quickly detecting methane plumes. Once a plume is identified, it alerts the ‘cue’ satellite, which carries out more advanced tasks such as detailed plume segmentation and estimating methane concentrations using a U-Net ML model.

Unlike traditional approaches, image analysis happens directly onboard, avoiding delays from sending images to ground stations for processing. To achieve this, the team built two ML-ready datasets, one with orthorectified images, and another with un-orthorectified images that are more suitable and realistic for onboard implementation. These datasets were used to train three models, bypassing the need for image correction and reducing inference time.

The datasets have been shared with the community, and the models are being optimised for spacecraft limitations in computing power, memory and energy. This system makes it possible to detect methane and other GHG leaks quickly, helping policymakers hold polluters accountable and support efforts to reduce emissions.

“We’re motivated to show how AI’s powerful predictive and insight-extracting toolbox can make a significant difference to how we monitor and manage our planet. What’s exciting about this year’s research products is that we are showing how multi-instrument methods and context-aware AI can be harnessed to make a dent in open problems – such as rapidly determining the anatomy of a cyclone or identifying erroneous greenhouse gas emissions from orbit. If you are a tech optimist – which we are – you will see that the puzzle pieces for a ‘mission control for Earth’ are now within our reach,” commented James Parr, Founder and Chief Executive Officer at Trillium Technologies.  

Nicolas Longépé, Earth Observation Data Scientist at Φ-lab, is ESA’s Technical Officer for the initiative: “The FDL sprint format works because it brings together experts from different fields to collaborate intensively and prototype solutions quickly. By combining domain specialists, AI researchers, and technical mentors, we can tackle complex, carefully chosen challenges with real impact. These three sprints fit perfectly into the Earth Action paradigm we pursue at Φ-lab, moving beyond passive observation towards proactive insights and decision-making for a more resilient planet.”

To know more: ESA Φ-lab, Trillium Technologies, FDL ESL AI SOTA Live Showcase

Photo courtesy of Trillium Technologies

Advancing AI for Earth observation at the REO workshop

Posted on by mavelar

The first ‘REO: Advances in Representation Learning for Earth Observation’ workshop will bring together researchers and practitioners from machine learning, computer vision, and Earth sciences to advance the development of robust, interpretable, and scalable models for monitoring our planet. The ‘Call for Papers’ submission deadline is 20 October 2025.

(Updated on 15 October 2025)

Taking place at the Bella Center Copenhagen on 6/7 December 2025, the Representation Learning for Earth Observation (REO) workshop – part of EurIPS, a European conference officially endorsed by NeurIPS – will gather experts from machine learning, computer vision, and Earth sciences to present the latest research, discuss real-world scientific uses, and share innovative system designs.

With massive, diverse datasets from satellites and other sensors becoming widely available – and with the rise of general-purpose foundation models – Earth observation faces new opportunities and complex challenges. But how can we best combine these various streams of information to create useful applications?

The development of representation learning algorithms that understand raw Earth observation data with minimal human instruction is gaining traction beyond university labs. This interest is highlighted by projects from technology leaders such as Google DeepMind’s AlphaEarth, ESA-IBM’s TerraMind, AllenAI’s Earth System, or Meta’s DINOv3.

This growth calls for more focused discussions on how to develop, deploy, and use these powerful models. The workshop will address fundamental questions like “Where is the field today, and what steps should the community take next?”, “What are the biggest hurdles in getting computers to effectively learn from Earth data?” or, given the trend towards general-purpose, one-for-all AI models, “What is the role of specialised approaches for Earth science?”

Participants are invited to present their novel work as extended abstracts or discuss recently published work that is relevant to the workshop. The ‘Call for Papers’ submission deadline is 20 October 2025. While the current deadline is set, organisers advise potential contributors to check the workshop’s website for any possible updates.

The topics are broad and exciting, including new approaches in machine learning for Earth observation, such as self-supervised, multimodal, and domain-adaptive models. Experts will discuss the combination of AI with physics, and the integration of established models into AI pipelines to get better predictions and understand the uncertainty in their results.

A major focus is on ecology and environmental monitoring, covering essential tasks like tracking changes in land use, mapping biodiversity, estimating forest biomass, and assessing the conditions of soil and vegetation.

Technical discussions will also focus on the difficulties of remote sensing data processing, such as combining different types of sensors and ensuring consistency between different satellites.

Discussions on data curation and accessibility will cover how to build fair, accurate, and easily accessible global datasets for research, ultimately driving real-world innovations in applications like mapping urban areas or monitoring natural disasters.

Leading scientists and industry experts will give keynote presentations: Gustau Camps-Valls from the IPL lab of the University of Valencia, Michal Kazmierski from Google DeepMind, Julia Gottfriedsen from OroraTech, Bertrand Le Saux from the European Commission, and Ankit Kariryaa from the University of Copenhagen.

“REO will provide an amazing opportunity for machine learning researchers and practitioners that are interested in Earth observation to find each other in Europe,” commented Ruben Cartuyvels, Internal Research Fellow at ESA Φ-lab. “The current trend in AI4EO of representation learning with foundation models of increasing size leaves many open questions, and fruitful community exchange is essential to take steps towards answering those”.

Interested parties can find out more about this workshop and submit their abstract here.

This workshop is being co-organised by researchers from ESA Φ-lab, the University of Copenhagen, the Technical University of Berlin, IBM Research Europe and ENPC.

To know more: REO Workshop

The banner image contains modified Copernicus Sentinel data (2024), processed by ESA

Leadership and technology: AEE boosts Spain’s resilience against wildfires

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Given the scale of the recent wildfires that have significantly affected Spain’s land and ecosystems, the Spanish Space Agency (AEE) has taken the initiative to strengthen the country’s capabilities in prevention, detection, and response. The objective is clear: to turn the challenge into an opportunity to bolster prevention, detection, and response capabilities, ensuring that Spain has the most advanced tools to protect lives, infrastructure, and the environment.

In collaboration with the European Space Agency (ESA), through its ESA InCubed programme, AEE is launching a pioneering national call for the development of innovative Earth Observation applications.

Read the full article (in Spanish) on www.aee.gob.es.

Improving precision nitrogen management with Messium

Posted on by mavelar

Messium is improving agricultural practices with advanced hyperspectral satellite data. Co-funded by the ESA InCubed programme, the company developed a tool that provides farmers with frequent, accurate insights into crop nitrogen levels and optimal fertiliser use, helping to boost yields, cut costs, and minimise environmental impacts.

Nitrogen is one of the most essential nutrients for crop growth, playing a central role in plant development, yield, and quality. In that sense, nitrogen fertilisers are crucial for boosting land productivity and sustaining global food demands.

However, the average global Nitrogen Use Efficiency (NUE) on crops is around 45%, with more than half of the applied nitrogen fertiliser lost as nitrous oxide emissions or leached in the form of nitrate into drinking water sources, contributing to groundwater contamination and surface water eutrophication.

Behind this nitrogen loss is the imprecise nature of fertiliser application. Farmers often apply nitrogen at incorrect amounts and times, a practice driven by a lack of real-time data on a crop’s specific needs. To improve both the sustainability and profitability of modern farming, a shift is required – one that moves away from relying on broad, imprecise fertiliser application toward more targeted, data-driven approaches.

Messium, a UK-based start-up, emerges as key player in precision nitrogen management, by using hyperspectral satellite data and artificial intelligence to assess the nitrogen status of wheat crops and address sub-optimal nitrogen use in farming – something that was not possible with previous multispectral/NDVI-based approaches. Nitrogen, like all chemical elements on Earth, reflects and absorbs radiation in a specific set of wavelengths, creating a unique spectral signature – a ‘fingerprint’ – that is identified by hyperspectral satellite technology.

Messium’s methodology is built on real-world data: 20000 geo-referenced samples from wheat crops were collected, matching the collection with hyperspectral satellite imagery. These samples were then analysed to get precise measurements of nitrogen and biomass. Together, this information was used to train Messium’s unique machine learning models, giving them the ability to accurately analyse crop health from above.

Messium makes crop growth models a viable tool for farmers: the company’s innovative hyperspectral solution provides real-time, in-season data on a crop’s nitrogen percentage and biomass, filling the critical data gap that previously rendered these models unusable for decision-making. Messium integrates this live information with weather, soil, and farm management data to create a comprehensive picture of crop health and nutrient needs. From this, growth models predict the crop’s maximum and most profitable yields, calculate the precise amount of fertiliser required, and can even forecast changes in crop status.

Another key point of Messium’s approach is the nitrogen dilution curve, which maps a crop’s nitrogen percentage against its biomass to determine if it has a nitrogen surplus or deficiency, indicating the ideal time for fertilisation. By combining the timing insights from the dilution curve with the optimal quantity from growth models, Messium optimises the amount of fertiliser and timing of application, increasing the average NUE to 80-85%.

The company follows a B2B2F (business-to-business-to-farmer) model: it provides fertiliser companies and precision agri-tech start-ups with nitrogen estimation insights that are seamlessly integrated into their platforms. Then, these partners deliver Messium’s data to end-user farmers and agronomists through their established networks, allowing weekly, more precise fertiliser recommendations without requiring any behavioural changes.

Messium became one of the leading players in the use of hyperspectral technology for agriculture: last year’s trials across Europe and Australia, using more than 13,000 lab-validated crop samples, found that over 50% of fields were incorrectly fertilised, leading to wasted input costs and unnecessary emissions. Messium’s technology enables a data-driven approach to tackle these inefficiencies, supporting commercial farmers as well as broader food security and net-zero objectives.

“At a time when Europe’s food security and sovereignty are more vital than ever, optimising nitrogen fertiliser use is key. At the same time, tackling harmful nitrous oxide emissions and nitrate leaching is essential to reaching net zero,” commented Vishal Soomaney, co-founder and CTO of Messium.

This start-up has achieved remarkable success through its own innovative approach, with the ESA InCubed programme providing valuable technical support and co-funding that helped accelerate its growth. Having reached a minimum viable product with InCubed in February 2025, Messium has secured £3.2 million in private investment and is now starting an extension of its product with InCubed in 2026.

Its success does not stop there: Messium has been collaborating with Open Cosmos – another InCubed-supported company – as a user of the HAMMER hyperspectral datasets, highlighting the importance of the InCubed ecosystem to find new customers, strategic opportunities, and valuable peer-to-peer feedback.

“With ESA InCubed’s support, we’ve turned Messium from a proof-of-concept into a commercial solution that helps farmers boost profits, cut emissions, and protect soil health for future generations. This collaboration has fostered strong partnerships with organisations like Open Cosmos and shown the real-world impact of space-enabled innovation. We’re excited to continue working with the ESA team to scale these solutions across Europe”, added Vishal.

Crop nitrogen (left, in %) and biomass (right, in kg/ha) in a field under analysis. During the season, the percentage of nitrogen in the crops can vary from 6 to 1%, and crop biomass can go as high as 16 t/ha. Messium’s in-depth analysis of a field at any point in the season allows for better nitrogen management. Credits: Messium analysis of Open Cosmos hyperspectral data.

Michele Castorina, Head of the Φ-lab Invest Office and InCubed Programme Manager, commented: “The collaboration between these two InCubed-supported companies is a clear indication of the programme’s success. InCubed cultivates an ecosystem where these ideas can connect, grow, and create new commercial value. By enabling the development of Messium’s product, we have demonstrated how European space technology can be transformed into a viable business proposition. Their solution is a perfect example of the innovative synergy we foster, showing how InCubed’s support further attracts significant investment needed to scale.”

“At Open Cosmos, our mission is to tackle Earth’s most pressing challenges with actionable data and connectivity from space,” stated Alberto Perez Cassinelli, Vice President of Data at Open Cosmos. “By providing Messium with our advanced hyperspectral data from our OpenConstellation, we are empowering their nitrogen analysis technology to deliver real value to wheat farmers worldwide. This collaboration demonstrates how space-based innovation can translate into practical, real-time insights that improve agricultural efficiency, sustainability, and food security.”

The banner image shows a NDVI-based approach from multispectral satellite imagery previously used by farmers to assess the status of their crops (left) vs. crop nitrogen (kg/ha) provided by Messium, based on hyperspectral satellite imagery (right). In the right image, lower crop nitrogen levels are represented in red and higher crop nitrogen levels in blue. Messium’s weekly insights provide the nitrogen percentage in the crop, the biomass of the crop (t/ha), and the total nitrogen in the crop (t/ha), all at a 5 x 5 m resolution.

To know more: ESA Φ-lab, Messium

Photo courtesy of Messium

A bold new chapter for AI4EO with ‘ESA Φ-lab Challenges’

Posted on by mavelar

With a new look and the same ambition, the rebranded ‘ESA Φ-lab Challenges’ return with a fresh momentum, inspiring the Earth observation and AI communities to drive innovation through a new series of impactful competitions.

Earth observation (EO) is a powerful window that shows how the physical, chemical, and biological systems of our planet are interconnected. Until now, initiatives like ESA’s AI4EO have demonstrated how the combination of remote sensing technologies and AI can reveal hidden patterns and drive environmental, technological, and social innovation at a larger scale – from measuring biodiversity and soil health, to urban city planning or disaster response.

But to keep up with the evolving nature of innovation, we must also broaden our approach. This is why AI4EO is evolving into ‘ESA Φ-lab Challenges’. While AI is a fundamental technology, it is just a piece of a bigger puzzle. This new initiative will open the door to a wider range of cutting-edge technologies and approaches, encouraging innovation in all areas of Earth observation.

At the same time, these challenges are a platform for researchers and innovators to showcase their work, contribute with practical solutions to shared global issues, and help build a dynamic and engaged Φ-lab community.

Ready to make a difference? Here are three challenges you cannot miss:

From orbit to action: AI for Earthquake Response

    What if you could help first responders and support life-saving decisions right after an earthquake?

    Earthquakes are among one of the most unpredictable and destructive natural disasters, capable of destroying buildings, severing power lines, and bringing entire cities to a standstill in seconds. In the aftermath, time is critical and swift action is needed to contain further destruction, rescue survivors and restore order.

    Despite having access to terabytes of high-resolution satellite imagery, mapping affected areas still relies heavily on human interpretation, making it a time-consuming task when there is no time to lose. Together with Earth observation data, artificial intelligence emerges as a promising tool to automate and potentially accelerate disaster response.

    To support humanitarian and disaster relief efforts, ESA Φ-lab and the International Charter ‘Space and Major Disasters’ invite data scientists, AI researchers, students, geologists and developers around the world – solo or in a team – to join the ‘AI For Earthquake Response’ challenge.

    This initiative challenges you to develop state-of-the-art AI models that will automatically detect damaged vs. undamaged buildings, by analysing pre- and post-event satellite imagery. Participants will have exclusive access to a curated archive of multi-mission, high-resolution satellite imagery collected from previous Charter activations. All the EO data products of the virtual constellation used in past Charter activations concerning earthquakes are seamlessly ingested and processed by the on-line platform ‘Charter Mapper’, and made available through the Earth Observation Training Data Lab (EOTDL).

    This challenge foresees two main phases: one ‘training and live scoring phase’, where participants will have the possibility to train and test their models on partially annotated scenes (closing on 5 September), and a ‘stress test phase’, where participants will have to deal with fully annotated imagery from previously unforeseen sites, like in a real earthquake scenario.

    A webinar about this challenge is available here. The deadline is 15 September 2025, 17:00 CEST. Winning models will gain visibility in open-science forums and may be considered for integration into the ESA Charter Mapper, potentially becoming tools used by the Charter community in future disaster response activations. The first, second and third place will be awarded € 3000, € 2000 and € 1000, respectively, during the 54th Charter Meeting, from 6 to 10 October 2025 in Strasbourg, France.

    HYPERVIEW2: explainable artificial intelligence

      Earth observation is transforming agricultural practices by providing timely, large-scale insights into crop health, soil conditions, water availability and land use/land cover. As these Earth observation systems rely increasingly on AI to process vast amounts of data, it is essential that the models used are not only accurate but also explainable.

      Explainable AI (XAI) ensures that farmers, agronomists, and decision makers can understand and trust the reasoning behind these outputs. This transparency is key to building confidence in digital tools, allowing for their responsible and effective use in agriculture.

      Following the success of the HYPERVIEW challenge in 2022, the HYPERVIEW2 challenge is now back to develop new XAI systems applied to agriculture, using airborne hyperspectral images, Sentinel-2 multispectral images and PRISMA hyperspectral images.

      The goal is to develop an XAI model to estimate the concentration of six important contaminants/trace elements in soils – Boron (B), Copper (Cu), Zinc (Zn), Iron (Fe), Sulphur (S) and Manganese (Mn) – using Earth observation imagery. In the right balance, these elements boost plant health, productivity, and resilience to stress – important information that farmers need to optimise crop nutrition and yield.

      This challenge was launched by Φ-lab, together with KP Labs, the Warsaw University of Technology, and the Poznan University of Technology. The deadline for applications is 14 September 2025 and the award ceremony will take place at the EASi Workshop, during the European Conference on Artificial Intelligence, from 25 to 30 October in Bologna, Italy.

      PANGAEA: testing geospatial foundation models’ capabilities with a cutting-edge benchmark dataset

        If you want to dive deeper into benchmarking or tackle targeted geospatial tasks, the PANGAEA challenge will be the right one for you.

        PANGAEA is a highly curated, comprehensive benchmark dataset for Earth observation, designed to evaluate the performance of machine learning models across a broad range of geospatial tasks, such as land cover classification, change detection, environmental monitoring, and multi-sensor/multi-temporal analysis, among others.

        What makes it so unique is its diversity and structure: while it covers a wide spectrum of resolutions, sensor types, and temporal layers, it also provides a standardised protocol for evaluating the performance of a model, which is crucial for comparing results from different researchers, institutions, and AI approaches. Additionally, PANGAEA is designed to test and refine geospatial Foundation Models, a new generation of AI models with a wide range of applications across Earth observation.

        This will be an open-ended challenge: participants will have the opportunity to continuously explore, experiment, and iterate their models over time. Within this challenge, there will be regular Data Sprints: short, high-intensity mini-challenges that will focus on specific real-world tasks using the PANGAEA dataset, with clear goals and metrics, and their own prize pool and recognition opportunities. These are ideal for teams looking to make a mark, try something new, or just have fun competing under pressure.

        The community should stand ready: the next Data Sprint will be announced later in 2025, promising fresh challenges, new opportunities, and a chance to shine.

        You can know more about these three challenges here.

        ‘ESA Φ-lab Challenges’ is an initiative created by ESA Φ-lab and implemented by Novaspace, Planetek Italia, Sinergise, GMATICS, and EarthPulse.

        To know more: ESA Φ-lab, Φ-lab Challenges

        Photo courtesy of ESA Φ-lab Challenges

        Help ESA redefine the future of space computing

        Posted on by mavelar

        Due to the growing volume of data produced by Earth observation (EO), traditional computing architectures struggle to process information efficiently and promptly. To mitigate this issue, prepare Europe for the future of space computing, and grow from Earth observation into Earth action, ESA is seeking innovative mission concepts that use disruptive computing paradigms, potentially coupled with matching sensing technologies that could either bring new capabilities for Earth-orbiting satellites, or significantly improve current mission constrains. 

        Artificial intelligence (AI) and novel computing paradigms such as quantum, photonic or neuromorphic computing have the potential to transform space-based applications by dramatically increasing mission autonomy and decision making without humans. To consolidate Europe’s position as a leader in sustainability and remote sensing, ESA is launching the new SysNova challenge “Innovative mission concepts enabled by disruptive computing paradigms“.

        The call builds on multiple past and ongoing initiatives at ESA. “Through missions like Φ-sat, OPS-SAT, and initiatives such as 3CS, ESA has explored the benefits of embedding intelligence in orbit. In parallel, disruptive paradigms like quantum and neuromorphic computing have shown potential to enhance processing of vast amount of data efficiently. Yet, few have examined how these technologies could redefine entire missions. It’s time to take that next step”, says Gabriele Meoni, Innovation Officer at ESA Φ-lab and one of the campaign managers.

        Read the full article on www.esa.int.

        Living Planet Symposium Extra News: Day 5

        Posted on by mavelar

        ESA’s Living Planet Symposium came to a close today, concluding a week of networking, discussions and meeting of curious, scientific minds.   

        Today, one of the focal points was thermal imaging instruments, which are critical for monitoring land-surface temperature – and will be carried on upcoming missions such as the upcoming Copernicus Land Surface Temperature Mission. ESA’s Soil Moisture and Ocean Salinity (SMOS) mission celebrated passing its 15-year milestone in orbit – the mission has helped improve weather and climate models.

        Three new contracts were signed for ESA’s InCubed programme, which is central to the agency’s efforts to turn promising concepts into successful Earth observation services, strengthening Europe’s position in this rapidly evolving sector. 

        Read the full article on www.esa.int.