ESA’s first Earth Observation Commercialisation Forum took place at ESA Headquarters in Paris on 30–31 October 2023. The event saw investors, institutions, entrepreneurs and different-sized companies from the Earth observation sector come together to discuss the commercial potential and challenges of Earth observation. Revisit the event by watching the streaming replay.
In his opening address, ESA’s Director General, Josef Aschbacher, said, “Advancing commercial space in Europe is one of the key components of Agenda 2025, which I set as an ambitious vision when I took over the position of ESA Director General.
“The fast-growing Earth observation sector has an abundance of possibilities that private businesses can capitalise on, from satellites and ground infrastructure through to value-added services that address real-world needs with information from space.”
At a recent showcase event, FDL Europe presented the fruits of this year’s summer research sprint. With technical and financial support from ESA Φ-lab, the team demonstrated how digital twins and foundation models can enable solutions in the areas of early detection of solar events, data gathering for disaster management, and facilitating downstream applications based on Synthetic Aperture Radar (SAR) data.
The Frontier Development Lab (FDL) Europe is a collaboration that works with ESA and a number of commercial partners such as Google Cloud and NVIDIA. The initiative focuses on accelerated research that applies artificial intelligence (AI) to space science in order to push frontiers and develop new tools that help solve major human challenges.
Φ-lab spearheads the collaboration within ESA, giving strategic and expert input into FDL Europe’s annual development cycle and individual projects. Each year, FDL Europe puts machine learning specialists together with Earth and planetary scientists for an intensive summer research sprint, drawing on bold thinking and rapid iteration and prototyping to produce stimulating outcomes.
For the 2023 run, the FDL Europe experts’ focus was heavily driven by the power of emerging AI technologies, as Head of the Φ-lab Explore Office Pierre Philippe Mathieu explains: “Foundation and large language models are examples of exciting new methodologies that are radically changing the way we – and machines – retrieve and interface with data. Part of FDL Europe’s remit is to apply these techniques safely and ethically for the benefit of humanity, and the three challenges this year were selected for their potentially wide-ranging impact in protecting our planet.”
Challenge 1: creating an SSA twin for space weather
The first FDL Europe team was tasked with creating a Space weather Situational Awareness (SSA) twin for solar events. Early detection of space weather is crucial for safeguarding both terrestrial and orbiting infrastructure, an endeavour that ESA’s Vigil mission will take on by providing an unprecedented view of the sun from its orbit at the fifth Lagrange point. But understanding the propagation of coronal mass ejections (CMEs) is complex, and Vigil’s distance from the Earth will limit its connectivity.
The team on this challenge developed a machine learning pipeline that leverages the advantages of edge computing in space with a CME-aware compression model, significantly reducing the downlink bandwidth requirements and the delay in alerting dangerous events. On the ground, their SSA twin can provide a three-dimensional reconstruction of solar activity through a combination of physics-based equations and Neural Radiance Fields, a deep learning method for synthesising 3D views of complex scenes by optimising an underlying continuous volumetric scene function using a sparse set of 2D input views. The result amply attests to the power of onboard intelligence paired with digital models.
Challenge 2: building a foundation model adaptor for disasters
As the recent growth in AI chatbots has shown, Large Language Models (LLMs) are having an enormous effect on society as a whole, but their ability to act as a knowledge store, summarise a large array of inputs and adapt to unseen tasks is also profoundly influencing software development. The second FDL team took on the challenge of harnessing the possibilities of LLMs for collating and interpreting information on current and past disasters, providing reliable and detailed reporting to authorities.
The team chose to focus on floods as one of the most prevalent and damaging classes of extreme weather events. While flood relief decision-making can often be hampered by the time and resources required to bring all the relevant insights together, the FDL team’s foundation model combines Earth observation (EO) data, flood prediction and mapping models, human-in-the-loop inputs and weather monitoring systems to create accurate, instantaneous flood reports through natural language processing. A prototype of the interface can be seen at floodbrain.com.
Challenge 3: a foundation model for analysing SAR EO data
With its all-weather capabilities, SAR remote sensing is an essential tool for Earth observation. However, in addition to the extensive preprocessing required, SAR data is difficult for deep learning to adapt to, and existing deep learning models struggle both to remain robust and to function reliably over new regions or different time frames.
The third FDL Europe team sought to develop SAR foundation models that could be generalised to a multitude of analysis tasks. The resulting pipeline was flexible enough to handle the huge breadth of data from SAR imagery and was also fine-tuned on a variety of labelled downstream tasks, including processing complex data and extending models across time and space domains. As a forerunner of a full foundation model for SAR, this pipeline has pioneered the way for a potentially transformative asset for the data-science community.
Giuseppe Mandorlo is the Project Manager for Vigil at ESA and so naturally was following the development of Challenge 1 particularly closely: “The results achieved by the FDL Europe Heliophysics team are extremely impressive – even more so when you take into account the short duration of the sprint. Some of the findings are truly astounding and could influence numerous aspects of the Vigil Project, from the selection of instrument imaging detector bands right up to the design of the overall Space Weather Network architecture.”
“All three of these challenges can be seen as precursor projects that lay the groundwork for the further development of key AI technologies for EO and science more generally,” added Φ-lab data scientist Nicolas Longépé. “The combination of multi-disciplinary research teams and internationally recognised mentors has led to remarkable outcomes and much food for thought, not least the fact that the user community for EO data will now include not only humans but also chatbots.”
A video of the showcase is now available, and the full report will be published on fdleurope.org shortly. Researchers interested in joining FDL Europe 2024 can now register their interest.
ESA’s first-ever Earth Observation Commercialisation Forum will open its doors at ESA Headquarters in Paris on 30 October. Registration is still available for this premier two-day event, which will bring together institutions, investors and businesses to explore the commercial potential and funding landscape in Earth observation.
The forum is open to all Earth observation (EO) stakeholders, including entrepreneurs, start-ups, established companies and public and private investment bodies. Attendees will be treated to keynote addresses from ESA speakers such as Director General Josef Aschbacher, Director of Earth Observation Simonetta Cheli and Director of Commercialisation, Industry and Competitiveness Géraldine Naja, along with representatives from the European Commission, venture capitalists and industry leaders.
The speeches, panel discussions and networking sessions will provide a unique opportunity to understand the market trends, major drivers and challenges in commercial EO. With such a wealth of opportunity for connecting up the many and varied players in the sector, the event is sure to be the go-to platform for delving into the state of the art and direction of travel in commercial Earth observation. Full details can be found on the dedicated website.
Register for the Earth Observation Commercialisation Forum here.
As part of the Italian National PhD in Earth Observation scheme, coordinated by Sapienza University of Rome, ESA is supporting 10 industrial research fellowships in trailblazing areas such as data fusion, edge computing and artificial intelligence (AI). Driven by the need to nurture new talent in Italy to create the Earth observation experts of tomorrow, the PhDs will involve the analysis and use of Earth observation data, and in particular Italian capabilities such as the IRIDE constellation, across a variety of applications, ranging from crisis management to climate change and agriculture. Each fellowship will include a six-month placement within Φ-lab at ESA’s ESRIN establishment near Rome.
Earth observation (EO) is key to monitoring our planet and guiding our society towards a more sustainable future. While the demand for space-based information to address global challenges such as climate change is rapidly growing, it is increasingly difficult to find the right talent for combining the necessary cross-disciplinary skills, including the understanding of physics, geoinformation processing, AI and computer science. EO scientists need to be able to draw on these fields in order to turn Big Data into new, sound scientific knowledge and information services.
In recognition of the importance of EO and the need to develop a skilled workforce to make the most of existing and upcoming Italian EO capabilities, the Italian University and Research Ministry (MUR) has recently supported the creation of the National PhD in Earth Observation (DNOT). DNOT aims to provide training and integrated skills for young researchers in EO, geomatics and geoinformation in response to the need to train professionals with transverse and integrated capabilities in EO and computer science, along with specific application, administrative and legal skills.
Tomorrow’s EO workforce will need to enhance the already existing services and design new ones, in close collaboration with actual and potential users of EO data. To this end, DNOT is fully integrated with the Copernicus Academy and offers a scheme to enhance knowledge through real hands-on experience with selected industrial partners.
ESA is one such partner, and together with the DNOT network has set up fellowships for 10 PhD researchers. The fellowships will be based at various universities across Italy, comprising Sapienza University of Rome, IUSS di Pavia, Università di Bologna, Università di Firenze, Università di Napoli Federico II, Università di Padova and Università di Pavia. The aim is to address a variety of EO applications ranging from data fusion to edge computing and new data products to support the understanding and better management of natural disasters, climate change, water cycles, landscape evolution and farming. A particular focus will be on using the upcoming IRIDE constellation to create new synergistic products with existing European EO assets such as Copernicus.
The cohort of researchers will also have the opportunity to spend six months at ESA Φ-lab over the course of their PhD, in order to bring new experiences and technologies like AI into the heart of their research. Φ-lab is a powerful enabler of innovation and groundbreaking research in Earth observation, and its areas of interest marry well with the topics chosen for these 10 positions.
Applications are encouraged from graduates in mathematics, statistics, physics, chemistry, geosciences, engineering and computer science who are keen to help shape the future of Earth observation. Details can be found on the fellowship call webpage (reference D – DM117).
Continuing its joint initiatives with ESA Φ-lab, UNICEF is appointing two researchers to work on a project that forms part of the UN Secretary-General’s Digital Cooperation Roadmap. The project maps current access to electricity and the Internet for schools around the world in support of an ambitious UNICEF target to provide connectivity for every child by 2030.
Around half of the world’s schools have no Internet access, and 1.3 billion children do not have connectivity at home. The result for those young people is fewer opportunities to learn and fulfil their potential.
In an effort to close this digital divide, UNICEF and the International Telecommunication Union have created Giga, a global initiative aimed at connecting every school to the Internet by 2030. Giga recognises that connecting schools enables children to develop digital skills and access online learning, while also providing wider connectivity benefits for businesses and services in the surrounding communities.
A crucial step in reaching Giga’s goal is to understand the current connectivity status, but many governments do not have comprehensive information on the locations of schools in their country or whether schools have electricity or Internet access. With its expertise in interpreting satellite-derived data through artificial intelligence, ESA Φ-lab is extremely well placed to offer a helping hand in this area and already has experience of fruitful collaboration with UNICEF in research on predicting dengue fever outbreaks.
In a project with Giga that profiles school catchment areas to predict grid connectivity, Φ-lab is employing techniques such as Support Vector Machines and Multi-Modal Deep Learning Networks to analyse both Earth observation and terrestrial datasets. “We set out to answer a number of questions that would improve today’s information and deliver comprehensive, credible data on schools around the world,” explains Φ-lab researcher Casper Fibaek. “We’ve already used our models to validate current UNICEF data on school coordinates and have identified 65 000 incorrect locations in Brazil, for instance. We’re now looking at estimating the student count per school by combining catchment-area modelling with population maps.”
The project is about to benefit from two new colleagues, both visiting researchers from UNICEF. The first appointee is Abi Riley, who after completing a Masters degree in mathematics in the UK is currently working on a PhD on spatio-temporal methods for environmental health modelling. The second researcher will be announced in the near future. Abi and her colleague will be working on measuring the likelihood of schools being connected to the Internet and mains electricity network through such diverse sources as NASA’s VIIRS Nighttime Imagery, Copernicus Sentinel 2 and auxiliary data on mobile phone usage.
“Abi will be most welcome in our very collaborative and catalytic research space,” added Φ-lab AI Applications Lead Rochelle Schneider, who also led the multi-award-winning dengue project with UNICEF. “I’m sure both she and the second appointee will make a remarkable contribution to a project that demonstrates Φ-lab’s continuing relationship with the UN for the benefit of disadvantaged communities.”
Dohyung Kim, Giga’s Lead Data Scientist, stressed the significance of having comprehensive data: “In our mission to connect every child to the internet by 2030, having actionable insights on Internet access is a fundamental component. This enriched data perspective allows us to understand and address the challenges faced by different schools and regions. We’re excited to continue our collaboration with our friends at ESA Φ-lab on this initiative. Furthermore, I am inspired by the fact that these two research posts reinforce our commitment to promoting opportunities for young scientists worldwide.”
At the International Geoscience and Remote Sensing Symposium (IGARSS) on 21 July, ESA Φ-lab presented the results of groundbreaking research in artificial intelligence (AI) aboard Earth observation satellites. Carried out by Oxford University and Trillium Technologies in collaboration with Φ-lab, the research successfully trained a cloud-detection Machine Learning model while in flight on a D-Orbit ION mission.
ESA has given considerable attention in recent years to Cognitive Cloud Computing in Space (3CS), with such initiatives as the Φsat missions and the 3CS Call for Ideas helping to push the boundaries of enabling ever-increasing computational power onboard Earth observation (EO) satellites. The D-Orbit Dashing Through the Stars mission was launched in January 2022 and included a number of service tests funded by ESA. Among these was a customisable Machine Learning (ML) payload which allows models to be uploaded, updated and run directly on the satellite.
Despite the models running on the satellite, model training would normally take place on the ground due to the computational load and the enormous datasets required. In a world first however, Trillium Technologies and Oxford University’s Department of Computer Science have trained one such model directly onboard during the D-Orbit mission. This development has momentous implications for remote sensing, not only in Earth Observation but also in deep space exploration, as onboard training allows models to adapt autonomously to both changing conditions in space and sensor calibration drift. This is all the more important when the communication channel between the spacecraft and ground is limited due to distance and/or bandwidth.
To overcome the resource constraints of onboard training for ML models, the research group adopted an innovative approach involving an initial ML model known as RaVAEn. This model specialises in efficiently compressing EO images to just a few kilobytes, reducing the data to a ‘latent space’ representation. The key advantage of this methodology lies in the ease with which the constrained satellite hardware can handle the compact latent space. Unlike the original large and data-intensive imagery, the compressed representation is significantly smaller and more manageable.
Illustration of the training data for the model (left) and the resulting predictions from new data (right). Detected clouds are indicated with red dots.
The full paper on the research will be published soon at ieeeigarss.org.
“RaVAEn first compresses the large image files into a vector of 128 numbers, keeping only the most relevant and informative content,” explains Vít Růžička, the project lead for Oxford University and a former Φ-lab visiting researcher. “By employing RaVAEn to compress the images, a second tiny ML model can work with the compressed latent space and perform onboard training and cloud detection without overwhelming the satellite’s resources.”
Following this initial demonstration of onboard training capabilities with base-level cloud detection, model development will now continue towards more challenging feature detection.
ESA data scientist Nicolas Longépé is leading the research on edge computing at Φ-lab and gave a talk on the results at IGARSS: “This activity received an enthusiastic response at the symposium, with the success of the RaVAEn compression capabilities opening avenues for rapid, computationally efficient training of models directly on the satellite. The results are also significant in terms of the federation aspect of 3CS, as we envisage the enticing prospect of intelligent, autonomous constellations with compressed but reliable data being exchanged within the fleet.”
The Earth Systems Predictability (ESP) Forum took place in May with support and major contributions from ESA Φ-lab. The event saw academics, institutional representatives and industry specialists come together to explore how the combination of Earth observation (EO) and artificial intelligence (AI) can inform data-driven decision-making on climate issues. The initial findings of the forum have now been published.
“The impact of our failure to care for our planet is now self-evident on a daily basis, underscoring the fundamental role of Earth observation in increasing awareness, helping to forecast trends and guiding policy on the climate crisis. AI can and does assist us with the considerable computational challenges associated with modelling Earth systems. Creating a sustained dialogue between experts in their respective fields will undoubtedly contribute to scaling and developing our predictive capabilities, and the ESP Forum was an exciting and valuable step towards that goal.” – Jonathan Bamber, Professor of Glaciology and Earth Observation at the University of Bristol and member of the ESA Advisory Committee for Earth Observation (ACEO).
The current catastrophic wildfires and extreme weather in southern Europe have sparked renewed discussions on the need for climate mitigation. Clearly climate change resilience planning and rapid disaster response will continue to be a central focus for society over the coming decades, driving the need for increasingly reliable and comprehensive Earth systems predictability. Initiatives like ESA’s Digital Twin Earth will provide a progressively more accurate picture of natural and human activity on our planet, but a gap exists between the knowledge gained from such models and the necessary action that should result from that knowledge.
Organised by Trillium Technologies in partnership with ESA Φ-lab and Oxford University, the ESP Forum was set up to build a cohesive vision on Earth systems predictability between data scientists, data users and decision makers. In a series of preliminary and main workshops, an interdisciplinary cohort came together to define the opportunities and challenges of developing ESP through the twin enablers of AI and satellite-derived data. The subject matter was divided into the three principal themes of Twinning and Simulation, Integrating Knowledge and Decision Intelligence, with participants at each session tasked with examining the practical steps required to establish and maintain a functioning and trusted ESP system.
The preliminary conclusions of the gathering have now been published. For the Twinning and Simulation theme, the forum emphasised that ESP technologies that combine EO data, fast simulations and robust machine learning models have a great potential for enhancing decision making at all levels, but these technologies must be deployed carefully to encourage adoption, scaling and impact. EO tools need to be accessible to a broad range of stakeholders, including for instance local populations and indigenous peoples, who in turn must be involved in creating shared knowledge tools. A holistic approach towards the simulation of interconnected systems will allow users to visualise consequences and outcomes more fully.
The Integrating Knowledge group discussed the role of Foundation Models and Large Language Models (LLMs), which offer a tremendous opportunity to build accessible and democratic expert systems for ESP. A key recommendation was to build LLMs that are continuously updated concept engines, with continuous learning/unlearning as a driver. The subject of stakeholders was also addressed by this group, including the proposal that semantic layers should be investigated so that jargon is not a barrier to communication, together with creating a broad advisory committee for knowledge systems in order to engage marginalised groups and vulnerable populations.
Under the Decision Intelligence theme, the participants stressed that AI should be seen as a joint decision-making paradigm, although integrating humans into hugely complex, multivariate and rapid decision scenarios will require innovation in how we interface with AI-derived recommendations. Disciplines from ESG (Environment, Social and Governance) best practice may be usefully applied to AI4EO, but the nuanced considerations that these areas require have so far been beyond the capabilities of machines. However, the technology is improving and therefore so is the ethical reach of the decisions that AI can support. The group concluded that ultimately, extending this moral remit to the decisions society needs to make to avoid the worst effects of climate change is where the greatest potential goal for AI4EO lies.
The full provisional findings are detailed on the forum webpage.
Kirsten Dunlop, CEO of Climate-KIC and keynote speaker for the Integrating Knowledge theme, emphasised the importance of the timing of the event and its findings: “We are at a critical juncture in terms of on the one hand, the rapid rate of global temperature rises and on the other, the exponential increase in data and knowledge available for decision making. With its broad spectrum of expert contributors, the ESP Forum was able to identify both the potential and the pitfalls of Earth system models for raising awareness and enabling more effective decision making in climate action.”
“Given our remit of transformational innovation and advanced computational research in Earth observation, the ESP Forum was a natural fit for us,” commented Head of ESA Φ-lab Giuseppe Borghi. “We were delighted to have contributed to the event and the discussions, and I’m convinced that the conclusions and directions to be set out in the final report will provide the building blocks for a true symbiosis of Earth system prediction and fact-based climate policy making.”
The Trans-Atlantic Training course (TAT 2023) took place in the Czech Republic from 27 June to 1 July and included presentations and tutorials from current and past Φ-labbers. Organised by ESA, NASA and the Charles University in Prague, the course was aimed at educating early-career scientists and post-graduate students on remote sensing for environmental monitoring and modelling.
TAT has been running since 2013 with the objective of providing training activities for young scientists in the field of Earth observation (EO), with a particular emphasis on remote sensing of land-cover change and ecosystem dynamics. The forum shares and discusses advanced space research through a series of workshops, with this year’s edition dedicated to Synthetic Aperture Radar (SAR), passive optical sensing and lidar for forestry, agriculture and hydrology.
Attendees from 18 countries took part and were able to gain a detailed picture of the state of the art in satellite-derived environmental measurement and prediction. The week was split between the cities of Prague and Brno and included insight from a number of global experts in the field.
The expert input included a significant contribution from ESA’s Earth Observation Programme Directorate. Scientific Coordinator Francesco Sarti was part of the TAT organising committee and kicked off Day 1 with an outline of the Agency’s current and forthcoming EO missions. Next was a session introducing Φ-lab and its activities, with talks from Digital Technologies Engineer Bertrand Le Saux, InCubed Officer Albin Lacroix and other Φ-labbers. The session began with a comprehensive overview of how the Explore Office’s research is transforming Earth observation through the application of artificial intelligence, quantum machine learning and other computational methodologies. This was followed by a presentation on the scope, benefits and successes of the ESA InCubed programme.
Day 2 featured a key lecture on applying SAR data time series to forest monitoring. Given by former Φ-lab visiting researcher Daniel Paluba, the workshop was largely based around work carried out at ESA and included two practical sessions, covering topics such as processing Copernicus Sentinel data and comparing Classical and Automatic Machine Learning approaches. This and the other ESA-related presentations were very well-received by the course attendees, with the Φ-lab sessions in particular giving a glimpse into real-world opportunities in EO research and commerce.
“I think it’s crucial that Φ-lab contributes to educational events such as TAT,” Bertrand Le Saux reflects. “Not only is it a pleasure for us to share details of our research and industry support with such an enthusiastic and energetic audience, but I also feel we are helping to plant the seeds for the EO scientists and entrepreneurs of tomorrow.”
The Italian region of Emilia-Romagna was devastated by severe floods in May 2023, claiming lives and displacing thousands of people, resulting in an estimated €8.8 billion in damages. With the region still grappling with the aftermath, satellites have been instrumental in assessing the damages of the affected areas.
Between 16-18 May 2023, 350 million cubic metres of water, equivalent to six months’ worth of rain, fell within 36 hours across Emilia-Romagna, one of Italy’s most important agricultural regions. The heavy rain led to the overflow of 23 rivers across the region, affecting 100 municipalities and triggering more than 400 landslides, which in turn damaged and closed off hundreds of roads.
At a recent award ceremony, Φ-lab announced the four winners of the AI4EO Call, a competition launched in conjunction with the We Make Future event. The top entries received a range of prizes, including an all-expense-paid trip to the ESA EO Commercialisation Forum in October.
As a seed bed for innovation in commercial Earth observation (EO), ESA Φ-lab actively promotes and encourages ideas from start-ups and entrepreneurs. We Make Future (WMF) is the largest digital and social innovation festival in Southern Europe, and so provides an ideal forum for Φ-lab to interface with today’s and tomorrow’s success stories in the space sector. In fact ESA has enjoyed a major presence at the gathering since 2020, and this year’s edition in Rimini in Italy featured a popular ESA booth with exhibits that included activities, products and mock-ups from Φ-lab. The multitude of visitors to the booth comprised enthusiasts, start-ups and companies among others, with each taking the opportunity to interact with Φ-labbers and other ESA representatives.
A notable attraction at this year’s event was the AI4EO Call, a joint initiative of Φ-lab and the organisers of WMF. The competition concerned applications of artificial intelligence (AI) and data processing in aerospace and EO and aimed to reaffirm the value of these sectors in international development and the protection of our planet. Entries were assessed by a panel consisting of ESA and industry representatives, based on criteria including project feasibility, degree of innovation, competitive positioning and potential for further development.
Sixteen of the start-ups were shortlisted and invited to WMF to pitch their proposals to the panel. At a dedicated ceremony in the ESA booth, Φ-lab AI Ecosystem Manager Sabrina Ricci announced the four winning applications:
FlyPix AI, a geospatial platform that extracts insights from satellite and drone imagery, enabling customers to detect and segment objects of interest, identify their characteristics and monitor changes and anomalies over time
SaferPlaces, an AI-based digital twin solution that uses satellite and climate data to deliver flood risk intelligence for urban environments
Terroir from Space, a service for the wine industry that both detects unexploited planting sites and monitors existing vineyards through AI processing of EO data
Latitudo 40, an analysis engine that draws on Deep Learning algorithms to provide customers with satellite-derived information on topics such as land use, carbon sequestration and coastline erosion
The first-prize winners, FlyPix, won a trip to the ESA EO Commercialisation Forum in October, where they will participate at an ideas-pitch session with private investors. Other prizes for the runners-up included access to business and technical coaching on EO and a subscription to the Sentinel Data Hub.
“We’re truly grateful to have had the opportunity to take part in the AI4EO competition at WMF 2023 and were overjoyed to be selected as the winners,” commented FlyPix co-founder Sergey Sukhanov. “Not only did this experience allow us to showcase our progress, but it also provided a platform for networking with other participants and exploring potential collaborations. In addition, the EO Commercialisation Forum will be a fantastic chance for us to present our product to a new audience.”
Head of the Φ-lab Invest Office Michele Castorina was impressed by the competition’s take-up: “There has been a striking response to the AI4EO Call, with an extremely broad range of ideas that amply demonstrate the vigour and continuing growth of European innovation. We’ve also had a great deal of interest shown in the ESA InCubed programme, giving a number of possibilities for future co-funding of EO start-up activities.”
