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Category: Philab

A thunderous shift in foundation model architecture with THOR

Posted on by mavelar

Foundation models are enabling new ways to use Earth observation data, but most existing models struggle to handle data from diverse sensors and are limited to fixed patch sizes. This makes them hard to use in real-world applications that require flexibility. Funded by ESA Φ-lab and developed by the Norwegian Computing Centre, THOR is a new foundation model designed to overcome both the challenges of heterogeneous inputs and rigid deployment constraints.

Foundation models are driving a paradigm shift in Earth observation, moving the field away from specialised models towards general-purpose geospatial intelligence. Although they promise to revolutionise the way we interact with satellite data, most current foundation models are architecturally rigid.

This means they are trained using a fixed input image size and a fixed patch size (the size of small, non-overlapping segments into which input images are divided before being fed to the model), making it more difficult to process data that differs, even slightly, from the format they saw during training.

Their rigidity creates a bottleneck for data-efficient adaptation: when the workflow breaks down the data into smaller patches, it produces a low-resolution sequence of tokens – units of data that foundation models process to understand the input they were given and then generate an output. Subsequent, dense pixel-level tasks like segmentation will then require large, complex decoders to upsample features. These decoders often require large amounts of data for fine-tuning, undermining the efficiency of foundation models.

Inspired by the Norse god of thunder and his legendary hammer, THOR (Transformer-based foundation model for Heterogeneous Observation and Resolution) is a versatile multi-modal foundation model that will shatter these shortcomings. This model has been developed by the Norwegian Computing Center, funded and supported by ESA Φ-lab through ESA’s Foundation Models for Climate and Society (FM4CS) project.  

THOR is the first foundation model with an architecture that unifies the 10 – 1000m ground sampling distance range of Sentinel-1, -2 and -3, including the OLCI (Ocean and Land Colour Instrument) and SLSTR (Sea and Land Surface Temperature Radiometer) sensors.

This model has been trained on the LUMI high-performance computer using the THOR Pretrain dataset, a 22TB-dataset that has been aligned spatio-temporally and across modalities, and that contains diverse land cover products, digital elevation models, and ERA5-Land variables. By incorporating a randomised patch size and input image size during pre-training, THOR becomes ‘computer-adaptive’.

Other state-of-the-art models like TerraMind, DOFA or Copernicus-FM are flexible in handling diverse inputs, but not so versatile when it comes to deployment. These models have a fixed internal resolution, meaning that, for very fine‑grained tasks like detailed floods or crop boundaries, they often rely on large, complex task‑specific decoders to recover detail.

Instead of locking the model into a fixed image size and resolution, THOR can change its internal resolution at inference time, allowing users to trade accuracy for computational cost without retraining the model: coarser patches could be used for faster, global analyses, while smaller patches can be used for more detailed, local maps.

This way, THOR solves both input heterogeneity and deployment versatility, focusing on making a single model adaptable and efficient across resolutions, data availability, and deployment constraints. THOR achieved state-of-the-art performance and demonstrated its superior data efficiency in the PANGAEA 10% benchmark, a standardised, open-source benchmarking framework designed specifically to evaluate the performance of geospatial foundation models (GFMs). The 10% benchmark refers to a specific, low-data evaluation scenario within PANGAEA designed to assess the effectiveness of GFMs when they are trained using only 10% of the labelled data for downstream tasks. 

Valerio Marsocci, Internal Research Fellow at ESA Φ-lab, comments the importance of THOR for real-world scenarios: “With dense, high‑quality features produced directly from the encoder, THOR often requires much simpler downstream models, which improves robustness and reduces costs. By providing a flexible pre-training starting point, we empower scientists to solve both local and global problems – whether it is mapping disasters or monitoring crop health – without needing to reinvent the architectural wheel.”

For Arnt-Børre Salberg, Chief Research Scientist at the Norwegian Computing Center, THOR sets a new standard for foundation models in the European space ecosystem: “We developed THOR to be a global ‘go-to’ foundation model for Earth observation. This open-access tool transforms satellite data into vital intelligence for maritime security, hydropower energy management and emergency preparedness against floods and avalanches, being an essential tool for a safer, more sustainable future driven by Norwegian innovation.”

THOR is helping Norway consolidate its strategic position in the Arctic region, according to Dag Anders Moldestad, Lead, Earth Observation at the Norwegian Space Agency: “Norway occupies a unique vantage point in the Northern Hemisphere. For us, satellites are not just tools, but our eyes on the ground.”

“What makes THOR a game-changer is its flexibility. It allows us to develop and deploy services in real time with significantly less computing power, so we can respond to crises as they happen. In disaster management, where every second counts, or in tracking the rapid shifts of our climate, THOR provides the speed and efficiency necessary to turn raw data into valuable information”, Moldestad added. 

Find more information about THOR’s technical details in this arXiv paper. The model and pretrain dataset are now available on Hugging Face. Its source code and TerraTorch extension are available on GitHub. A showcase of THOR can be found here.

To know more: FM4CS, ESA Φ-lab, Norwegian Computing Center

Photo courtesy of Unsplash/Mark Kӧnig

A new training explored AI in Earth observation

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From 8 to 11 December, ESA Academy’s Training and Learning Facility in Belgium hosted the pilot edition of the Disruptive Innovation and Commercialisation in Earth Observation Training Course. Organised in collaboration with ESA Φ-lab, this first edition brought together 30 Master’s and PhD students from 16 different nationalities, creating a vibrant and diverse learning environment.

One of the aspects that made this course unique was its dual focus. Participants were trained not only in Artificial Intelligence (AI) applied to Earth observation, but also in the business and commercialisation strategies necessary to turn innovative ideas into viable ventures. This combination of technical and entrepreneurial skills was designed to push students beyond traditional academic boundaries.

“The unique combination of AI, business and Earth observation made it truly one of a kind,” said one student. “Collaborating with motivated participants and learning from the ESA Academy and Φ-lab experts pushed me to think beyond disciplines.”

Read the full article on www.esa.int.

Breaking the satellite trade-off: AI creates near real-time 3D cloud maps

Posted on by mavelar

Clouds play a critical role in Earth’s climate system and are a major source of uncertainty in climate projections. The vertical distribution of ice and water particles in clouds impacts their radiative properties and with that Earth’s energy balance. Recent research also showed that the internal properties of clouds in tropical cyclones influence how storms intensify. Yet satellites face a fundamental trade-off: systems that measure vertical structure lack continuous coverage, while those with continuous coverage cannot see inside clouds.

Now, research conducted through the Earth Systems Lab research programme, funded through the ESA Φ-lab and involving former ESA research fellow, Dr Anna Jungbluth, has developed a breakthrough machine learning framework that translates two-dimensional geostationary satellite imagery into detailed three-dimensional cloud maps in near real-time. Published in November 2025, the study demonstrates for the first time the ability to create global instantaneous 3D cloud reconstructions, with particular success in mapping the internal structure of intense tropical cyclones.

Read the full article on www.climate.esa.int.

Photo courtesy of Unsplash/Zbynek Burival

New ESA-GEOSAT deal to empower space solutions

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ESA and GEOSAT have formalised their commitment to strengthening the space industry by signing a Letter of Intent, promoting entrepreneurship and advancing the development of innovative space solutions.

The latest company joining the portfolio of ESA’s Partnership Initiative for Commercialisation (EPIC) is the Portuguese company GEOSAT, one of Europe’s leading providers in Earth Observation (EO) satellite imagery and data analytics. GEOSAT provides very-high resolution (VHR) optical satellite data in Europe, being certified as a DPS Category 2 Provider (European Earth Observation Established Data Suppliers) and developing innovative EO products and services.

This partnership with GEOSAT will benefit companies supported by ESA Φ-lab, the InCubed Earth Observation commercialisation programme, ESA Phi-LabNET, ESA Business Incubation Centres (ESA BICs) and ESA Technology Brokers, operating under the broader ESA EPIC framework.

As an outcome of this Letter of Intent, GEOSAT will provide VHR data to ESA-supported start-ups, so they can test, validate and improve their services, along with technical mentorship and expertise, and joint outreach and networking activities to foster new opportunities and raise awareness about the societal value of Earth observation technologies. Further information on the collaboration and how to take advantage of the services provided by GEOSAT is now available here.

“By working with GEOSAT and opening access to their Earth observation constellation, we are allowing an easier access to data in order to improve solutions, in areas such as environmental monitoring, agriculture, infrastructure management, and maritime surveillance,” commented Michele Castorina, Head of the ESA Φ-lab Invest Office. “This collaboration not only benefits entrepreneurs and businesses across several sectors but also reinforces Europe’s competitiveness in the global space economy.”

To know more: GEOSAT, ESA Φ-lab, InCubed, ESA Phi-LabNET, ESA Business Incubation Centres, ESA Technology Brokers, EPIC

Photo courtesy of ESA

Earth observation indicators as the key to unlock the Global Goal on Adaptation framework

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The 30th Conference of the Parties (COP30), held in Belém (Pará, Brazil), is strategically focused on implementation, with the challenge of creating a definitive, measurable framework for the Global Goal on Adaptation (GGA). Directly addressing this issue, a new ESA Φ-lab co-led article published in Nature offers a timely intervention, showing how satellite-based Earth observation data can provide the objective, globally consistent indicators needed to achieve climate resilience. 

10 November marked the start of the 30th Conference of the Parties (COP30) in Belém, Pará, Brazil’s gateway to the Amazon rainforest. Regarded as a key point in the global climate agenda, COP30 is shifting the focus from ambition to implementation and accountability, to make the Global Goal on Adaptation (GGA) framework finally operational.

Established by the 2015 Paris Agreement, GGA seeks to improve the ability to cope with climate impacts, build systems that can withstand shocks, and reduce susceptibility to climate hazards. With negotiations culminating on a final set of indicators to measure the progress towards this goal, the success of the summit will lie on implementing a scientifically robust and actionable framework.

Directly addressing GGA – and with a perfect timing – a new ESA Φ-lab co-led article, “Earth observations for climate adaptation: tracking progress towards the Global Goal on Adaptation through satellite-derived indicators”, has just been published in Nature.  This article is the result of the ‘Using Earth Observation Systems to Improve Climate Adaptation Policy and Action’ forum held last year in Bern (Switzerland), hosted by the International Space Science Institute (ISSI).

As part of the work performed within ESA’s Climate Change Initiative (CCI), “the paper highlights Earth Observation’s strengths in providing objective, repeatable, and globally consistent data, while also acknowledging challenges related to data disaggregation, integration with socio-economic factors, and the need for long-term, robust baselines”, the authors stated.

This research details how Earth observation (EO) data are relevant across the entire adaptation cycle, from initial risk to long-term monitoring and evaluation, focusing on four key sectors covered by the GGA framework.

For agriculture, satellites can monitor water-based variables such as evapotranspiration and soil moisture, as well as the status of surface water storages, the evolution of agricultural pests caused by climate change, and shifts in agro-climatic indices like aridity.

Regarding ecosystems and biodiversity, EO is uniquely positioned to measure the extent and changes of ecosystems like coastal mangroves, which serve as natural defences against sea-level rise and storm surges. Adaptation actions like those targeting the climate change-exacerbated threats of pests, droughts, and wildfires, are essential to protect the diverse environmental and socio-economic functions of forests, which include the provision of raw materials for bioeconomy, serving as a wildlife habitat, prevention of soil erosion, and facilitating carbon sequestration.

Extreme events such as floods, droughts, heat waves, or hurricanes, can be monitored by EO technologies, which provide insights across the different stages of the disaster risk management cycle, from pre-event assessment to post-event recovery. Additionally, EO data can be used to quantify vulnerability through detailed mapping of inhabited areas, building footprints, roads, and critical infrastructure such as dams.

EO data are instrumental in monitoring health-related hazards, in particular heat extremes, infectious diseases, and air pollution from wildfires, being frequently used as the input for models to produce hazard or exposure maps. While satellite-based data do not directly capture health outcomes, they are a proxy to perform health assessments at different levels: individual, household, cohort, or administrative.

Despite its immense potential, the authors stress that EO is not a solution on its own and provide recommendations for both the policy and scientific communities. They strongly urge negotiators to integrate EO data into the final GGA indicator toolbox that is set to be adopted at COP30.

Simultaneously, the authors call on the EO community to focus on how to operationalise EO-based adaptation data and information to make them easily accessible to policy makers. They also recommend a substantial investment in end-user training and embedding geospatial data science experts within operational agencies, especially in vulnerable regions, as this is essential for effectively using EO data for adaptation solutions.

The article concludes by highlighting that EO data must be integrated with socio-economic and local data to ensure it accurately reflects the context of adaptation and does not overlook the vulnerability of specific, often marginalised populations. 

Rochelle Schneider, Copernicus and Destination Earth Ecosystem Operations Engineer and the second author of the paper, commented: “To track real progress on adaptation, we need data that peacefully crosses borders effortlessly. This is exactly what EO satellites provide — globally harmonised evidence to support collective action against climate change impacts.”

This Nature perspective serves as the foundation for other efforts underway at ESA Φ-lab: Diego Jatobá dos Santos, an International Research Fellow supervised by Rochelle Schneider, is working on a project to assess the climate risks faced by children under different climate zones and climate change scenarios in Brazil, in a fruitful collaboration with UNICEF.

Diego will investigate an adjustment in UNICEF’s Children’s Climate Risk Index (CCRI) for Brazil climate zones, using diverse geospatial datasets and predicting CCRI under different climate change scenarios, with CMIP6 and/or Destination Earth Digital Twin data.

Building on this effort, Φ-lab is currently recruiting a Research Fellow to work on Artificial Intelligence (AI) for Climate Adaptation. The new lab member will investigate how AI can play a significant role in climate adaptation, resilience and mitigation.

The full Nature article is available here.

To know more: COP30, ESA Φ-lab, UNICEF’s Children’s Climate Risk Index (CCRI)

The banner image features forests around the Capim River (Rio Capim) in Brazil. Contains modified Copernicus Sentinel data (2022), processed by ESA.

Less is more: the power of TerraMind in your pocket and in space

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On the last Earth Day, the European Space Agency (ESA) and IBM Research Europe launched TerraMind, a multimodal Earth observation foundation model. While powerful, the model’s need for large computing capabilities for fine-tuning and inference poses certain challenges, particularly in remote or resource-constrained environments. In October 2025, two lighter versions of TerraMind were released to be run on edge devices – like laptops or directly onboard satellites – enabling on-device, real-time analysis. The TerraMind Blue-Sky Challenge launched to even further improve TerraMind and has two new deadlines: 30 November 2025 and 31 January 2026.

Geospatial and Earth observation foundation models are crucial for overcoming global challenges. Pre-trained on vast, globally diverse datasets using self-supervised learning, these models learn a universal “language of Earth”, meaning that they can be quickly fine-tuned with minimal new data and supervised learning to perform a wide range of complex tasks, from disaster response and damage assessment to crop yield forecasting and wildfire spread forecasting.

This drastically reduces the cost, time, and data-labelling efforts required to create actionable insights, making complex Earth observation data more accessible for scientists, policymakers and communities worldwide.

As recalled during the last ESA-NASA International Workshop on AI Foundation Models for EO, the broader challenge now lies in moving beyond rapid-cycle prototyping toward the operational deployment of foundation models for real-world decision-making and societal benefits.

Achieving this requires designing models with deployment as a central consideration — ensuring they are efficient, accountable, and seamlessly interoperable with downstream systems such as digital twins, public dashboards, and early warning platforms. Enabling edge deployment, including onboard satellites, is vital for real-time analysis in resource-constrained environments.

To support this transition, building smaller but efficient models together with robust and scalable software stacks is essential to empower the broader community to adopt and apply these models effectively and responsibly.

In April 2025, ESA Φ-lab and IBM Research Europe launched TerraMind, a multimodal Earth observation foundation model. TerraMind is currently the best performing Earth observation foundation model, assessed by open community benchmarks such as PANGAEA, as it is the only model to outperform other traditional Earth observation methods with a frozen encoder strategy.

Six months later, two lighter versions of TerraMind – TerraMind.tiny and TerraMind.small – were released, specifically engineered to operate on normal or edge hardware devices. Despite their reduced size, these lightweight versions of TerraMind have little decrease in performance – compared with its full-scale version – allowing for model fine-tuning to any downstream use cases just with a standard computer, even without GPUs, or deploying the model to the ultimate edge, directly onboard orbiting satellites.

Performance of various TerraMind models (in blue) compared to other established foundation models (e.g., Prithvi 1.0, Prithvi-v2-300M), as assessed by the PANGAEA benchmark. mIoU (mean Intersection over Union) is a measure for performance in segmentation tasks. The higher mIoU value, the better a model performs.

Besides bringing Earth observation capabilities to edge devices, the creation of the ‘tiny’ and ‘small’ versions of TerraMind also lowers the entry barrier for Earth observation researchers, field workers, or smaller organisations. By drastically reducing the hardware requirements, anyone with a laptop can fine-tune these models and create new applications to better monitor Earth.

“The open-sourcing of the ‘tiny’ and ‘small’ TerraMind models is a game-changer for the entire Earth observation community. This is a clear step towards the true democratisation of planetary-scale foundation models,” commented Nicolas Longépé, Earth Observation Data Scientist at ESA Φ-lab.

“These lightweight versions shatter a barrier imposed by the lack of access to the latest, most powerful GPUs. They maintain industry-leading performance while running efficiently on edge devices and, most importantly, they move the power of cutting-edge AI from the exclusive domain of research centres and companies to the hands of the many who need it most,” Nicolas added.

Although the ‘tiny’ and ‘small’ versions of TerraMind represent a major leap in accessibility, innovation does not stop there: the TerraMind Blue-Sky Challenge, organised by ESA Φ-lab and IBM Research Europe, welcomes innovative ways to push TerraMind beyond “just another fine-tune”, whether it is prototyping a new multimodal workflow, exploring Thinking-in-Modalities, pushing the limits of these tiny but mighty models, or inventing a never-seen geospatial application.

This bi-monthly award has two new submission deadlines – 30 November 2025 and 31 January 2026, 23:59 (AoE). Each winner will receive a € 1.000 cash prize, with a potential publication in a joint wrap-up paper and broad visibility across IBM, ESA, and the Earth observation community. More information about this challenge can be found here.

All versions of TerraMind can be found here. TerraMind was developed within FAST-EO, an initiative led by a consortium comprising DLR, Forschungszentrum Jülich, IBM Research Europe and KP Labs, and supported and funded by ESA Φ-lab.

To know more: ESA and IBM collaborate on TerraMind, IBM ESA Geospatial @ Hugging Face, TerraMind Blue-Sky Challenge

Photo courtesy of Unsplash/Conny Schneider

Four new initiatives to boost Spain’s Earth observation sector

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As the result of an ESA-dedicated commercialisation campaign for Spain, the InCubed Programme signed four new contracts with IVSEN, HAPSEYE, CrossBandInsights, and DVSTAI. From energy infrastructure monitoring to security and geospatial object detection, these projects reflect the growing impact of Earth observation data across key sectors.

Following the success of the last dedicated call for Spain, four initiatives signed a contract with the ESA InCubed programme. This call, launched in collaboration with the Spanish Space Agency (AEE), offered different levels of co-funding to develop innovative and commercially viable Earth observation products and services, while benefitting from the European Space Agency’s technical, commercial and financial guidance.

IVSEN is an advanced satellite-based monitoring solution tailored for energy infrastructure operators. It integrates a very-high-resolution payload (< 50 cm) with reduced mass and volume, along with agile observation modes for flexible operations. An on-board pre-processing algorithm works in tandem with the ground-based processing chain to generate specialised data products and analytics. This project is being developed by a consortium – SATLANTIS, Alén Space, DHV Technology, and GeoAI – with direct contributions from users such as Iberdrola to ensure the system meets real operational needs.

“IVSEN represents a strategic milestone for SATLANTIS, as it strengthens our capabilities in very high-resolution Earth observation — a core technology for the company’s future. We are grateful to ESA for their trust and support in driving this project forward, and for enabling us to deliver an agile solution that will help energy operators and other users monitor and safeguard their critical infrastructures,” stated Juan Tomas Hernani, CEO of SATLANTIS.

ICEYE delivers synthetic aperture radar (SAR) data worldwide through its fleet of satellites, supporting applications such as land use monitoring, border surveillance and environmental monitoring. To expand this capability, the company is developing HAPSEYE, a solar-powered, fixed-wing aircraft designed to operate at altitudes above 20 km for extended periods.

Equipped with a SAR payload, HAPSEYE will complement ICEYE’s satellite constellation by providing persistent, high-resolution imaging that overcomes current limitations in coverage and resolution. This next-generation platform will improve disaster response, security and environmental monitoring. The activity is planned to begin after the test campaign of HAPS Prototype-1, scheduled for late 2025.

“As a pioneer in SAR imaging radar satellite innovation, we are delighted to have been chosen for ESA’s InCubed programme in Spain. Initiatives like this are crucial for accelerating technological advancement and strengthening European competitiveness in the Earth Observation sector – objectives that resonate strongly with our mission at ICEYE. This commitment is underlined by the high-altitude platform station project we are taking on as part of the programme, designed to aid European natural disaster response and Earth Observation capabilities,” stated Lauri Väin, VP of High-Altitude Platforms at ICEYE.

TRE ALTAMIRA delivers satellite radar (SAR) displacement measurements and mapping solutions for sectors such as civil engineering, mining, oil, and gas. Its product, CrossBandInsights, enhances current single-frequency band interferometric SAR (InSAR) products, by combining X- and C-band observations with higher spatial and temporal observations to improve ground movement monitoring. This allows for engineering firms and authorities to detect subtle changes, supporting smarter infrastructure maintenance decisions and strengthening risk management with enhanced spatial and temporal coverage.

“InCubed Spain has given us the unique opportunity to turn our vision into a concrete product that will bring tangible benefits to the Earth observation market. CrossBandInsights addresses a critical need by merging multi-mission C-band and X-band InSAR data to provide more accurate and timely insights on ground deformation,” commented Roberto Montalti, Project Manager at TRE ALTAMIRA.  

“This innovation will support civil engineering companies and public authorities in ensuring infrastructure safety and resilience. We see this project as a clear example of how public funding can be effectively invested to foster innovation, create market-ready solutions, and strengthen Europe’s position in the space sector,” Roberto added.

Thales Alenia Space, a global leader in space manufacturing, has been delivering advanced solutions in telecommunications, navigation, Earth observation, environmental management, science and orbital infrastructures for over 40 years. Among its innovations is DVSTAI (Deeper Vision Self-Trained AI), an evolution of the SatHound project, designed to overcome the limitations of current geospatial object detection methods: traditional approaches often require expert intervention for model design, training, and deployment, making the process slow, costly, and vulnerable to risks such as unauthorised access or data leakage.

DVSTAI addresses these challenges by leveraging deep learning techniques, allowing even non-AI or non-Earth observation specialists to autonomously train and use models through a user-friendly software solution. These models can be tailored to specific applications, including object detection, change detection, and semantic segmentation.

“DVSTAI is a user-centric AI solution that empowers non-technical users to autonomously create, train, and deploy AI models for object detection and vision tasks over satellite imagery. It simplifies the process, reduces costs, and enhances security by eliminating the need for dedicated AI engineers to develop high performing vision models, making it an invaluable tool for EO analysts and service providers,” commented Julian Cobos, Product Line Manager at Thales Alenia Space Spain.

“Thanks to the ESA InCubed programme, Thales Alenia Space will develop new key capabilities for object detection in Very High Resolution (VHR) and Synthetic Aperture Radar (SAR) data and bring DVSTAI solution to the public Cloud in a Software as a Service (SaaS) model, making it accessible for any user to set-up object detection campaigns over open and commercial data sources,” Julian added.

To know more: ESA InCubed, Spanish Space Agency (AEE)

Photo courtesy of Unsplash/Chris Boland

ESA InCubed and UKSA fund five Earth Observation projects

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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