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Unmissable Φ-lab moments at LPS 2025

Posted on by mavelar

At this year’s Living Planet Symposium, ESA Φ-lab will present its innovations and initiatives at the forefront of Earth Observation. Make sure not to miss our key moments.

The European Space Agency’s Living Planet Symposium (LPS) is one of the world’s largest events dedicated to Earth Observation (EO). LPS25 – this year’s edition – will take place from 23 to 27 June, in Vienna (Austria), gathering scientists, policymakers, and industry experts to share the latest research, satellite-based applications, and innovative technologies addressing environmental and societal challenges.

As part of this dynamic programme, ESA Φ-lab will be actively involved, presenting its next-generation solutions at the intersection of EO, transformational innovation, commercialisation for human prosperity, climate action, and sustainability, among others.

Curious about Φ-lab? Make sure to pass by the Φ-lab corner at ESA’s stand (Main Hall, ground floor) to meet the team, discover how Φ-lab drives cutting-edge research and disruptive technologies in Earth Observation, and learn about opportunities for collaboration.

Here are Φ-lab’s must-sees:

1. The future of geospatial data discovery and use

The rapid growth of EO data availability calls for new approaches to efficiently manage, analyse and extract meaningful insights from heterogenous and enormous satellite datasets. In this context, self-supervised learning and foundation models are emerging as transformative tools, offering unprecedented capabilities for detecting patterns, changes, and anomalies across the planet.

Φ-lab has built a strong expertise in using powerful AI models. The latest example is the joint ESA/IBM Research Europe release of TerraMind, a next-generation geospatial foundation model designed to help us better understand and protect our planet.

AI is reshaping EO, enhancing data analysis, discovery, and interaction through multimodal data and language models. In the session “AI and Earth observation – where to now?”, Φ-lab Visiting Professors will share the latest advances and lead a thought-provoking debate on the future of AI in remote sensing.

During the session “Foundation Models for Earth Observation: Current solutions with less labelled data to improve environment monitoring and future perspectives to revolutionize geospatial data discovery and utilization”, you will learn about three of the latest Φ-lab-supported projects on the topic of foundation models for EO: TerraMind, FM4CS (Foundation Models for Climate and Society) and PhilEO.

EVE (Earth Virtual Expert) is a large language model (LLM) developed to support the EO and Earth Science communities. It builds on open-source LLMs, trained on billions of curated EO data tokens and fine-tuned with tailored datasets. Designed to assist both expert and non-specialists, EVE makes complex EO knowledge accessible to everyone through natural language processing. In the session “EVE: A Comprehensive Suite of LLMs and Data for Earth Observation and Earth Sciences”, attendees will discover how EVE was built, explore its capabilities, and learn how to interact with it for their own applications.

Ensuring AI technologies are explainable, trustworthy, and physics-aware is essential. “Explainable AI for Earth Observation and Earth Science” will explore cutting-edge advancements in Explainable AI methods across diverse data types, including SAR, optical, and hyperspectral data. Attendees will discover innovative strategies to bridge data gaps, address physical inconsistencies, and promote responsible, ethical AI use in support of Earth Action initiatives.

2. Advancing weather and climate forecasting with Machine Learning

The monitoring and prediction of Earth’s weather and climate systems have seen remarkable progress in recent years. With the growing availability of high-resolution satellite data and sophisticated in situ sensors, we have now access to an unprecedented amount of data about our planet’s interconnected systems. Machine learning and deep learning techniques are transforming the way we interpret, model, and forecast the complex dynamics of Earth.

“Machine Learning for Earth System Observation and Prediction” will bring together researchers exploring the latest AI-driven approaches in environmental science. It will highlight innovations in data assimilation, climate prediction, and the development of large-scale, data-driven Earth system models.

3. Investing in commercial ideas that change the way we see our planet

Great ideas need more than ambition. They need backing, and this is where the ESA InCubed programme steps in. By blending co-funding, technical expertise, and commercial and industrial guidance, InCubed is a key tool of ESA’s EO commercialisation strategy to effectively bridge the gap between vision and commercial success in the EO sector.

As the demand for agile EO solutions grows, public-private partnerships are emerging as a powerful model to accelerate innovation and optimise resources. “New approaches to support commercialisation” will gather industry and institutional voices to explore the opportunities of new approaches, but also address challenges such as goal alignment, intellectual property, and data access.

“Enhancement of EO products using advanced multi-instrument and multi-platform synergies” will focus on methods that exploit synergies between complementary observations, modelling and multi-sensor data, using data from missions like Copernicus’ Sentinels, EarthCARE, MTG, EPS-SG, PACE, among others.

“Commercial Earth Observation Missions: Embracing New Paradigms and Innovative Models” will explore new commercial EO mission concepts designed to meet both institutional and market needs. With examples of business models – from public-private partnerships to fully private ventures – this session will offer insights into the evolving commercial EO landscape.

Driven by new climate regulations such as EU ETS and CBAM, the demand for accurate GHG monitoring is rising. “Opportunities in the Earth Observation Market: A Focus on GHG Monitoring” will focus on the commercial opportunities at the intersection of Earth Observation and climate policy, featuring an overview of the regulatory landscape, and a panel discussion with EO companies developing services to meet emerging compliance needs.

4. Harnessing Quantum Computing for a smarter, greener future

Quantum Computing (QC) promises to process vast amounts of information more efficiently than classical systems, creating new opportunities for climate modelling, environmental monitoring, and the analysis of highly complex, interconnected natural systems. By accelerating data processing and enabling new types of simulations, quantum technologies could improve the accuracy of climate predictions and support more responsive decision making in the face of global challenges.

In the “HPC and Quantum Computing” Insight Session, experts will discuss how quantum technologies are beginning to transform the way we work with EO data. It will also explore hybrid quantum-classical approaches, which combine the strengths of both computing paradigms.

“Joint ESA-GRSS initiatives for the exploitation of Earth Observation data” will focus on the work developed by the Quantum Computing for Earth Observation Working Group, an initiative that is part of the IEEE-GRSS Technical Committee QUEST (Quantum Earth Science and Technology) and operated in collaboration with Φ-lab. This project fosters collaboration between the QC and EO communities and is working to turn the promise of QC into practical, impactful applications for EO, through joint research, open knowledge exchange and hands-on projects.

5. Smarter satellites, faster insights: inside the Φsat-2 mission

Designed to test new mission concepts and onboard data processing using advanced AI processors, ESA’s Φsat-2 is an innovative nanosatellite that runs multiple applications directly in orbit. Equipped with a high-resolution multispectral instrument, it supports tasks like cloud detection, vessel classification, wildfire monitoring and image compression.

“The ESA Φsat-2 mission: an AI empowered 6U Cubesat for Earth Observation” session will present the mission’s status, AI demonstrations, and opportunities for the community to engage. Make sure not to miss the Φ-lab-led presentation: “All4One or One4All? Tailoring Onboard AI with NAS and Foundation Models”.

6. Where future careers in Earth Observation begin

To secure the future of Earth Observation, it is essential to engage and inspire young professionals today. The “Exploring Space Opportunities with ESA Φ-lab and EUSPA: Pathways for Students and Young Professionals” session is designed for students and young professionals eager to enter the European space sector, with a focus on innovation, technology, and entrepreneurship.

The session will introduce two key institutions: ESA Φ-lab and EUSPA, the European Union Agency for the Space Programme, which manages operational EU space services like Galileo, EGNOS, and Copernicus.

The Grand Marathon, organised by Φ-lab, is an innovation challenge rewarding scalable, market-ready solutions addressing climate events and infectious diseases, with a focus on younger populations. Launched in November 2024 and held in partnership with Save The Children and Hello Tomorrow, the competition celebrates the power of AI-based technologies and blockchain for global resilience.

The “Grand Marathon Finalists pitching and award” session will host the final pitch between the two top teams – GEOMATYS and Plastic-i – who will receive € 50.000 each and compete for the € 150.000 first prize.

Join Φ-lab at LPS25 and take the opportunity to connect, explore new possibilities, and be part of the conversation driving the next wave of Earth Observation innovation.

To know more: Living Planet Symposium, ESA Φ-lab, TerraMind, FM4CS, PhilEO, EVE, InCubed, QUEST, Φsat-2

Photo courtesy of ESA

Join ‘Call for Φdeas’ and make your transformative mark in Earth Observation

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‘Call for Φdeas’ is a call for ideas sponsored by ESA Φ-lab to stimulate transformative innovation in the Earth observation sector. This call encourages the submission of groundbreaking ideas that can make an impact in scientific fields like Earth Science, green-tech, climate-tech, and sustainability, institutions, NGOs or in the commercial sector. Selected ideas can receive up to € 1.000.000 in funding and the deadline for submissions is 31 August 2025.

In a rapidly evolving world, Earth observation (EO) plays a vital role in understanding and addressing global and local challenges. To keep pace with emerging needs and technological advancements, it is essential to look for fresh perspectives and novel approaches. Funding calls such as ESA Φ-lab’s ‘Call for Φdeas’ create valuable opportunities to explore untapped potential for transformative innovation in the Earth Observation domain.

‘Call for Φdeas’ is open to research and academic institutions, NGOs, commercial entities (start-ups, SMEs and LSIs), international collaborators, among others, to propose ambitious, forward-thinking initiatives that will have an impact in scientific fieldslike Earth Science, green-tech, climate-tech, and sustainability, institutions, NGOs or in the commercial sector.

The main targets for this call are ideas with transformative potential, not incremental innovation. Selected ideas are expected to deliver significant technology progress and/or impact the reference sector/market/system by a different use of current technologies.

Selected ideas can be used to populate future ESA Φ-lab workplans or as input for other ESA programmes (e.g., FutureEO, InCubed). ‘Call for Φdeas’ offers a maximum funding of € 1.000.000 per idea and co-funding is encouraged. For more information, please refer to ‘Evaluation Criteria’ in the dedicated Call for Φdeas channel on the Open Space Innovation Platform (OSIP).

Ideas should fall into three categories: ‘Exploratory Ideas’ (to investigate novel, unconventional or unproven EO-related concepts, including technologies, mission studies or EO applications), ‘Capacity Building’ (to build the competences, techniques, or ecosystems needed to mature promising disruptive EO ideas), and ‘Innovation Impact’ (to translate a mature idea into a transformative solution ready for adoption for an identified use case).

This is a recurrent call and accepts new submissions twice a year. For 2025, a single round of submissions is foreseen, and the submission phase deadline is 31 August 2025 COB.

By encouraging diversity of ideas, ‘Call for Φdeas’ helps ensure that the Earth observation sector remains dynamic, relevant, and responsive to the complex realities of our planet.

To know more: ‘Call for Φdeas’ OSIP, ESA Φ-lab

Photo courtesy of ESA

Strengthening space ties: new ESA International Fellowship for a Brazilian researcher

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The European Space Agency (ESA) and Brazil have maintained a collaborative relationship in space exploration and technology over the years. In 2002, ESA and Brazil signed a Framework Cooperation Agreement to expand joint efforts in space science, Earth Observation, telecommunications, microgravity experiments, and life sciences, facilitating the exchange of experts and collaborative studies, and strengthening the scientific and technical ties between the two entities.

Since then, other joint initiatives followed. In 2011, Brazil’s National Institute for Space Research (INPE) became a member of the International Charter ‘Space and Major Disasters’, an ESA co-founded global initiative that provides rapid satellite data access to support disaster management efforts. In 2018, ESA and the Brazilian Space Agency (AEB) signed an Implementing Arrangement to establish and use telemetry and tracking facilities in Natal, Brazil.

In March 2024, Simonetta Cheli, Director of Earth Observation Programmes at ESA, and Clezio Marcos De Nardin, Director of the National Institute for Space Research, signed a Protocol of Intent to strengthen the relationship between ESA and INPE/AEB.

As part of the research outcomes stemming from the Protocol of Intent signed between ESA and INPE, Gabriel da Rocha Bragion, ESA International Research Fellow, will spend 12 months at ESA Φ-lab developing methods for estimating carbon stocks from biomass, using SAR data and machine learning techniques. 

Read the full article on www.eo4society.esa.int.

Emerging European thermal imaging firm enjoys global success

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OroraTech, a leading supplier of thermal sensing data and predictive wildfire solutions, has been subcontracted by Spire Global to develop a Canadian wildfire monitoring service as part of a major government contract. 

Spire Global, a space-based data, analytics and space services provider, is leading the project, with OroraTech – which has worked closely with ESA in recent years to hone its capabilities – preparing the constellation’s instrumentation. This marks an important milestone in the growth of the emerging Germany-based company. 

This achievement demonstrates the shared objective of ESA and the European Commission to empower growing European data providers to scale their operations and achieve commercial success in the global Earth observation marketplace. 

Read the full article on www.rapidresponse.copernicus.eu.

Norwegian EO industry lifts off with new ESA InCubed national call

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Norway-based companies of any size are invited to participate in the latest InCubed call by submitting proposals for the development of groundbreaking and commercially promising products in the Earth Observation (EO) field. The call opens on 15 April and the deadline for submissions is 27 May 2025 at 14:00 CET.

ESA InCubed is an Earth Observation commercialisation programme managed by ESA Φ-lab that aims to boost entrepreneur initiatives in the Earth Observation (EO) sector, supported by its signatory Participating States. With a focus on leveraging the benefits of EO data and services, InCubed provides co-funding for the development of any elements of the EO value chain, namely full satellites and constellations, platforms, payloads and instruments, ground segment-based systems, and downstream applications and value-added services. 

Depending on the type of activity, companies can apply for co-funding support and will be guided by ESA top-tier experts to create sound products/services from a technical, commercial, and financial standpoint, with ESA acting as the de-risking partner.

In collaboration with the Norwegian Space Agency (NOSA), the upcoming Norway national call will open on 15 April 2025 and has a budget of €2.1 million. Proposals should be focused in developing innovative and commercially successful EO products and services.

Norwegian companies with innovative ideas leveraging EO data or developing relevant EO technologies may apply. Universities and research institutes with no commercial interest in the project may be funded up to 100% of their costs if those do not surpass 30% of the total activity funding. Business ideas currently being funded by other ESA/NOSA programmes are not eligible for this call, unless for complementary tasks.

Interested Norwegian companies should submit an idea pitch on the Open Space Innovation Platform (OSIP), which will be ranked based on defined criteria, including the understanding of InCubed’s objectives; quality and completeness of the business and technical proposals; adequacy of the management approach, planning and co-funding; and level of experience. Qualifying pitches will be invited to submit a full proposal to ESA. Successful applicants will be contacted directly by ESA to discuss further contract negotiations. The first evaluation cycle will be in June 2025.

Interested companies can find out more about this call during the InCubed meeting at NOSA, in Oslo, on 7 April, and enrol via the NOSA dedicated link. The call opens on 15 April 2025 and the closing date for submissions is 27 May 2025 at 14:00 CET.

To know more: ESA InCubed, Norwegian Space Agency

Photo courtesy of ESA

Talking to Earth: a first-generation AI digital assistant

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A recent initiative funded by ESA Φ-lab focuses on creating an AI-powered digital assistant that allows users to access and explore complex EO data through a natural language interface. In the long term, the aim is to integrate this tool into digital twins of Earth, supporting decision-making in areas such as climate monitoring, disaster management and urban planning.

A digital twin of the Earth environment is an interactive “digital replica” that allows us to understand the various relationships between the physical and natural Earth environments and society. It enables scientists to quantify past, present and future events on our planet, integrating models, observations, and technologies such as Artificial Intelligence (AI) to improve our understanding of the human impact on global environment and society.

Through data and simulations, digital twins allow for real-time prediction, monitoring, control and optimisation of Earth’s natural and physical processes. Two related flagship programmes are the European Commission’s Destination Earth (DestinE) and the European Space Agency’s Digital Twin Earth (DTE).

In the past years, rapid advances in Earth Observation (EO) have led to an increase in the amount of available EO data to be processed for the benefit of society, creating an opportunity to harness the power of new technologies like AI. The growing European EO capability is delivering a unique and dynamic picture of Earth, but this information remains largely unexploited due to current limitations in querying and retrieval capabilities and does not include an appropriate interface for non-experts to interact with digital twins.

Technologies such as Computer Vision and Natural Language Processing – used for object detection/EO image segmentation and for interpretation of human language, respectively – have been treated as separate areas, without benefitting from each other. But what if we could use these technologies together to create a new way to interact with and understand EO data?

In that sense, ESA Φ-lab is funding the creation of a digital assistant interface for digital twins of Earth – Demonstrator Precursor Digital Assistant Interface for Digital Twin Earth (DA4DTE) – in collaboration with e-GEOS (Italy), the National and Kapodistrian University of Athens (Greece) and the Technical University of Berlin (Germany). Φ-lab has already a proven track record in the development of foundation models, which serve as the basis for digital assistants.

The developed digital assistant prototype interacts with users via two modalities, text and satellite images, and consists of four back-end engines: search-by-image, search-by-text, knowledge graph question answering (KGQA), and visual question answering (VQA) engines. These engines are orchestrated by the task interpreter to answer complex requests of users looking for EO data.

The Knowledge Graph Question-Answering Engine is built on a knowledge graph that integrates geospatial data from widely used geographical knowledge bases, such as OpenStreetMap, along with metadata from Copernicus missions. This knowledge graph is combined with Large Language Models (LLMs) such as Llama, GPT, and Mistral.

The search-by-image engine is based on a newly developed technique called Cross-Modal Masked AutoEncoder (CM-MAE). This method features modal-agnostic, self-supervised feature characterisation, making it well-suited for cross-modal image retrieval tasks. Additionally, the engine incorporates deep hashing modules to map cross-modal embeddings into compact binary hash codes, ensuring efficient and scalable data storage and retrieval.

In the end, the idea is that users, whether they are EO experts or not, will be able to perform a semantic query on EO data archives such as “Show me 3 pictures of rivers in Italy, with a vegetation coverage over 20%, taken after May 2020” or “Count the number of buildings in this area”. This digital assistant will help to answer questions in several EO-related data domains – agriculture, forest, urban, marine, cryosphere, among others – contributing to improved decision-making.

“As digital twins of Earth become increasingly sophisticated, the ability to interact with them is crucial. The digital assistant for Digital Twin Earth represents a major step forward in making complex Earth Observation data more accessible”, comments Nicolas Longépé, Earth Observation Data Scientist at ESA Φ-lab. “By allowing users to ask questions in natural language and receive insightful, data-driven responses, this tool lowers the barrier to entry and accelerates the use of EO data for decision-making. Whether it is for climate monitoring, disaster response, or environmental management, having an intelligent interface to navigate and interpret vast datasets is essential for informed action.”

All the developed back-end engines are available as open source with a permissive licence here. The precursor digital assistant prototype is available here. A presentation titled “A digital assistant for digital twins of the Earth” will take place during Living Planet Symposium, from 23 to 27 June 2025 in Vienna, Austria.

To know more: ESA Φ-lab, Digital Twin Earth, Destination Earth

Photo courtesy of Unsplash/Carl Wang

Where there’s smoke, there’s data: SeasFire’s mission to predict wildfires in Europe

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SeasFire, an ESA Φ-lab-supported initiative, uses cutting-edge deep learning algorithms to explore the spatio-temporal connections between Earth system variables and fire regimes, gaining valuable insights into predicting potential wildfires. This project is aligned with ESA’s mission to develop innovative applications of Earth Observation (EO) data that address important societal and environmental challenges. 

Planet Earth undergoes several complex physical processes that occur at variable spatial and temporal scales. Wildfires are notable examples of such processes, since they do not behave the same way in different areas and years. As major hazards, wildfires are deeply influenced by a combination of multiple human and natural factors, such as temperature, soil moisture, relative humidity, wind speed, vegetation – commonly referred to as ‘fire drivers’.

Wildfires disrupt natural ecosystems and cause the loss of lives, properties and infrastructure. Due to climate change, an increase in the number of fires in Europe and around the world is expected, with major wildfire events extending to evergreen forests and boreal regions. Therefore, it is important to improve our capabilities to anticipate fire danger and understand its driving mechanisms at a global scale.

SeasFire – Earth System Deep Learning for Seasonal Fire Forecasting in Europe – emerges as an innovative solution for fire forecasting. Supported by ESA Φ-lab and implemented by the National Observatory of Athens, the National Technical University of Athens, the Harokopio University of Athens and the Max Planck Institute for Biogeochemistry, SeasFire proposes to explore and capture the potential spatio-temporal asynchronous links between pre-occurring and non-overlapping fire-driving forces in the Earth system and European fire regimes to predict seasonal burned area extent in Europe.

How has this been accomplished? SeasFire has made use of two major advancements of our time, namely the availability of a huge amount of satellite data with good spatio-temporal resolution, and Deep Learning (DL) techniques that have proven capable of capturing the spatio-temporal interactions of Earth system variables, treating Earth as an interconnected system.

Some of the DL models developed in this project include an encoder-decoder architecture that takes as input snapshots of fire drivers and is trained to predict burned area patterns in the future; FireCastNet is a Graph Neural Network that can leverage local, mid-range and long-range spatial connections; and TeleViT is a transformer-based architecture, which combines information from local fire drivers and teleconnections to improve long-term forecasting.

Current CO2 estimates rely on factors such as burned areas, vegetation carbon stocks, and combustion completeness. While Machine Learning algorithms have been developed to forecast burned area patterns, prior estimates from vegetation carbon stocks and combustion completeness are model-based and assume fixed emission factors that may not accurately capture larger changes in carbon stocks over longer periods.

SeasFire overcomes these limitations by integrating Earth Observation (EO) data with climate datasets in a hybrid modelling framework. This approach combines process-oriented modelling with observation-based learning, enabling more accurate model parameterisation and reducing biases from model initialisation. By comparing existing carbon models with data from the Copernicus Atmosphere Monitoring Service (CAMS), SeasFire enhances the reliability and precision of carbon cycle predictions.    

The SeasFire DataCube, a public global analysis-ready and cloud-friendly dataset for seasonal fire forecasting, between the years 2001-2021 and at a spatio-temporal resolution of 0.25° x 0.25° x 0.25° x 8 days, includes a combination of variables describing seasonal fire drivers, namely climate, vegetation, oceanic indices, human factors, land cover and the burned areas. In the future, this datacube can also be exploited as a template for modelling different natural hazards like floods, heatwaves and droughts.

From this initiative resulted also an interactive toolkit that allows the visualisation of EO data and model outputs stored in a Zarr file, accessed via the SeasFire GitHub organisation. In this repository, it is possible to find all trained models regarding seasonal wildfire forecasting and modelling of CO2 emissions.

“This project explores a key gap by attempting to capture the interannual variability of seasonal, high-impact wildfire events — an area where traditional numerical models often fall short. By leveraging Deep Learning and teleconnections which dictate climate dynamics, we explore novel machine learning methods that treat the Earth as a system to enhance long term forecast capabilities. Moving forward, we aim to refine models for more precise regional predictions, establish clear benchmarks for comparing our models with existing and future approaches, and strengthen collaborations to validate and operationalise our methodology”, says Ilektra Karasante, SeasFire Project Manager.

“Φ-lab’s support has been essential from the project’s conception to its implementation. Beyond the initial trust in funding this high-risk/high-gain research, Φ-lab has further accelerated our developments by providing access to computational resources through the Network of Resources (NoR), fostered collaborations with leading scientists in the field, and enhanced the project’s visibility through ESA and ECMWF workshops, strengthening our research network and helping integrate our work into the broader scientific community. Through all the above Φ-lab-supported activities, SeasFire outcomes reached a much broader audience.”

Φ-lab hosted a workshop about “Innovations in Data-Driven Seasonal Fire Forecasting: From Models to Visuals” on 7 February 2025. Patrick Ebel, Internal Research Fellow at Φ-lab and SeasFire Technical Officer comments: “It was my pleasure being ESA’s Technical Officer for this activity and its enthusiastic consortium. SeasFire shows how recent advances in Deep Learning and weather forecasting can be harnessed to model wildfires and their impact to tackle one of the greatest challenges Europe will be facing in the coming decades under a changing climate. I appreciated the public’s scientific interest in SeasFire and look forward to future advances building on the achievements of the activity.”

To know more: ESA Φ-lab, SeasFire

Photo courtesy of Unsplash/Mike Newbry

P³ANDA receives second prize at the 2024 Telespazio Technology Contest

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On 28 January 2025, a group composed of one ESA Φ-lab Research Fellow, one Visiting Researcher and one Intern, was awarded the second place at the 2024 Telespazio Technology Contest (#T-TeC). The award ceremony was held in Brussels during the 17th European Space Conference, with the presence of ESA Director General Josef Aschbacher. Their project, P³ANDA, focused on the creation of an AI-powered compact instrument to capture panchromatic images, optimising the acquisition and processing of satellite data in real time.

The Telespazio Technology Contest (#T-TeC) is a global open innovation competition sponsored by Leonardo and Telespazio, aligned with Leonardo Group companies’ innovation needs, and designed to inspire young STEM students from universities worldwide and drive innovation in the space sector.

Its sixth edition brought together a record number of 114 participants, showcasing 29 proposals from 26 universities from 10 different countries. The 2024 edition awarded winners with cash prizes and the chance to transform their ideas into start-ups through acceleration and incubation programmes, helping them bring their projects to market.

The awards ceremony, held in Brussels during the 17th European Space Conference with the presence of ESA Director General Josef Aschbacher, showcased proposals in two categories: ‘Idea’ and ‘Prototype’. The ‘Idea’ category was designed for projects in the early stages of development, while ‘Prototype’ was reserved for more mature projects, in which participants presented advanced prototypes ready for testing and further development.

The teams tackled seven different challenges spanning various aspects of the space sector. The themes ranged from sustainability in space and Earth to advanced Earth Observation and geo-information services, in-orbit services, the circular economy of space, and much more. The competition showed a diverse set of forward-thinking solutions, emphasising their potential to drive meaningful progress, particularly in sustainability.

Roberto Del Prete (Research Fellow at ESA Φ-lab), Domenico Barretta (Visiting Researcher at ESA Φ-lab), and Alessandro Crispiels (Intern at ESA Φ-lab), won the second prize in the ‘Prototype’ category under the theme “Innovative Electro-Optical Technology Solutions for Remote Sensing.”

Left: P³ANDA team at the #T-TeC 2024 Ceremony Award, held during the 17th European Space Conference. Domenico Barretta (left), Roberto Del Prete (middle), Alessandro Crispiels (right). Right: Roberto Del Prete (left) with ESA Director General Josef Aschbacher (right). Luca Del Monte (not shown) was ESA’s representative at the 2024 T-TeC awards ceremony.

Their project, P³ANDA – Panchromatic Plug-n-Play AI-eNabled Data Assembly – integrates a panchromatic imager, an on-board processing unit that runs AI-based and advanced computer vision algorithms, and on-board processing tools in a compact 1U assembly, aligning with the operational needs of small-satellite integrators and Earth Observation service providers. The development of P³ANDA was supported by Ubotica Technologies, IMT, and XCAM.

Designing sensors requires a balancing trade-off among swath width, spectral content, and spatial resolution. While hyperspectral imagers capture and analyse detailed information across a wide range of wavelengths, at the cost of limited spatial resolution, panchromatic imagers collect more photons per unit of time, increasing the signal-to-noise ratio, which results in clearer images, crucial for detailed analyses.

Panchromatic imagers have also an increased modulation transfer function (MTF), which focuses on maximising spatial resolution by emphasising sharpness and clarity. An increased MTF enhances the satellite’s ability to distinguish fine details, essential to applications like target detection or precision mapping.

All in all, P³ANDA is an all-in-one solution: by being AI-ready, it reduces downlink requirements; it is easily integrated with other sensors and includes state-of-the-art lightweight deep learning models.

The team received a cash prize of € 6000 and the opportunity of pre-incubation with cesah GmbH to start their own start-up. They will also have the chance to compete for the incubation process with one of ESA’s Business Incubation Centres.

Roberto Del Prete, Research Fellow at Φ-lab and team leader, says that “This victory in the Telespazio Contest 2024 is not just ours — it belongs to everyone who supported and inspired us. We – Domenico, Alessandro, and I – are especially grateful to Φ-lab for providing the space where our idea came to life. This moment reaffirms the role of disruptive innovation and collaboration in driving the future of space technology”.

To know more: ESA Φ-lab, Telespazio #T-TeC 2024

Photo courtesy of Telespazio

New AI-powered insights with the latest Major TOM embeddings

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Building on the success of Major TOM’s (Terrestrial Observation Metaset) inaugural dataset release last year, ESA Φ-lab has launched the first global embedding dataset for Earth Observation (EO), in collaboration with CloudFerro. These embeddings deliver an efficient representation of vast volumes, enabling more precise and scalable analysis of satellite data.

March 2024 saw the release of Major TOM, a collaborative project designed to enable researchers to share, access, and integrate extensive EO datasets. Major TOM’s inaugural core dataset constitutes the largest machine learning (ML)-based collection of Copernicus Sentinel-2 images to date.

Less than one year later, ESA Φ-lab and CloudFerro revealed new Major TOM’s embedding expansions, which will improve the processing of complex information and drive advancements in ML, natural language processing, and computer vision.

With the massive and continuously increasing volumes of EO data in programmes like Copernicus, efficient vector representations are more necessary than ever. By encoding complex data into high-dimensional vectors, embeddings capture relationships and meaning, transforming natural language, images and other data types into a compact form that can be readily integrated in diverse AI pipelines.

This process enables machines to uncover patterns, similarities and connections with precision and accuracy in a manner agnostic to the downstream task. With embeddings, users can efficiently interpret key features of interest from satellite imagery, sensor data and geographic information systems, simplifying the analysis of spatial relationships and optimising time and resources.

This latest release consisted of more than 169 million embeddings, as the result of processing over 62 TB of raw data. Major TOM’s Embedding Expansions, now available for free on HuggingFace, include the Sentinel-2 Multispectral SSL4EO Model (Core-S2L1C-SSL4EO), the Sentinel-1 RTC SSL4EO Model (Core-S1RTC-SSL4EO), the Sentinel-2 RGB DINOv2 Model (Core-S2RGB-DINOv2) and the Sentinel-2 RGB SigLIP Model (Core-S2RGB-SigLIP).

Mikolaj Czerkawski, Internal Research Fellow at Φ-lab, was the leading researcher in this project: “Once applied at the full scale of Sentinel data archives, embeddings will fundamentally change the way users engage with Earth Observation data. This collaboration between Φ-lab and CloudFerro enabled a rapid delivery of an open-source prototype of this technology, showing how open data programmes like Copernicus can deliver further benefits to the global community beyond what was originally foreseen.”

Future work will focus on evaluating how Major TOM embeddings perform across a range of EO tasks, including pattern detection and predictive modelling, and on investigating other foundation models – such as MMEarth and DeCUR – to understand which the differences between how various models interpret EO data. The Major TOM dataset, now enriched with embeddings, will also be made available on the CREODIAS repository, offering open access to researchers and promoting collaborations within the EO community.

To know more: ESA Φ-lab, CloudFerro

Photo courtesy of ESA/Mikolaj Czerkawski

Exploring new frontiers with QC4EO at ESA Φ-lab

Posted on by mavelar

ESA Φ-lab has recently launched a new industrial activity in line with the Quantum Computing for Earth Observation (QC4EO) initiative. ‘Towards Operational Quantum Computing for Earth Observation’ focuses on the implementation of QC4EO use cases on quantum hardware with an operational focus. The aim is to demonstrate to the community that this revolutionising technology is quickly progressing with an increasing and positive impact on EO.

Quantum Computing (QC) is a hardware revolution that is increasing our ability to do much more than a conventional digital computer could. Together with AI, one of the most important software revolutions of our times, they are forming an extremely powerful alliance.

But how will QC change the computation paradigm? The first – and most obvious answer – is through its speed. Quantum computers will be able to perform specific calculations much faster than classical computers. They will also perform simulations of complex systems with a much higher degree of accuracy.

When it comes to energy efficiency, quantum computers will be designed to use fewer resources than classical computers and will open a range of new opportunities for problem-solving (e.g., factoring large numbers, optimisation in Complex). Brought together, these features will make QC a very appealing technology for Earth Observation studies.

Aligning with the ongoing technological disruption, ESA Φ-lab is exploring the expected revolution that Quantum software and hardware promises and that will positively impact EO and Earth Action, through the blend of QC4EO industrial, exploratory, and community-building activities.

On industrial activities, and building on the success of the QC4EO and QA4EO studies, Φ-lab has started a large project: ‘Towards Operational Quantum Computing for Earth Observation’ emphasises the application of Quantum Computing in Earth Observation (QC4EO), with a focus on hardware implementation and operationalisation. This initiative tests and implements quantum-based algorithms, featuring at least two use cases, one of which is associated with Digital Twin Earth.

This project highlights the swift progress and transformative potential of quantum technologies in the Earth Observation domain. Supported by the Foresight Element of FutureEO Block 4, it seeks to foster innovation and advancement in the sector.

Other industrial activities by Φ-lab include a recent co-funded activity, in collaboration with the University of Bari Aldo Moro, for the use of Quantum Machine Learning applied to SAR data for ground motion measurements. While previous activities are still under execution (e.g.,‘Quantum Computing and Artificial Intelligence for Earth Observation’ with CERN), Φ-lab and its partners – Forschungszentrum Jülich GmbH, Jagiellonian University and Nicolaus Copernicus Astronomical Center – have successfully closed relevant activities on the field.

Currently pushing the boundaries of this research field, Φ-lab is developing new exploratory activities focused on Hybrid Quantum Machine Learning for land cover and land use classification, EO image generation, noise filtering in EO image datasets, and prediction and forecasting.

Φ-lab also released an open-source Python library for QC4EO, integrating QC into deep learning frameworks like TensorFlow and Torch, and providing tools for designing and executing hybrid quantum algorithms. For more information on Hybrid Quantum Models, visit the library here.

The Φ-lab QC4EO network has recently experienced a significant growth, connecting around 40 experts on QC4EO and bringing researchers, research centres, universities and agencies together. Additionally, Φ-lab is organising a dedicated session on “HPC and Quantum Computing for EO” at the Living Planet Symposium, in Vienna, and will be present at the 2025 IEEE Geoscience and Remote Sensing Society (GRSS) High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Summer School.

Together with Gabriele Cavallaro, Visiting Professor at Φ-lab, the lab will be part of a new technical committee of IEEE GRSS about quantum technologies for EO (QuestTC). Alessandro Sebastianelli, Internal Research Fellow at Φ-lab, will be leading the working group – a branch of the technical committee – on QC4EO.

“At Φ-lab, we are very proud of this achievement. From building fundamental blocks like quantum neural layers to applying new quantum solutions in EO image filtering and forecasting, we are creating a new path in Quantum Computing for Earth Observation.”, comments Alessandro Sebastianelli. “This confirms the capability of Φ-lab to work on disruptive and revolutionary technologies, leading the R&D of Quantum Computing applied to Earth Observation.”

While advancements are being made in the fields of quantum-safe networks and quantum imaging, future research will bring insights in quantum navigation and simulation in chemistry and material sciences.

To know more: ESA Φ-lab, QC4EO

Photo courtesy of Unsplash/Nicolas Arnold