AI turns space data into solutions for Earth’s biggest challenges
AI is already embedded in everyday digital services, from curated news feeds to predictive text. While these tools feel close to home, this same technology is now reaching far beyond our atmosphere.
By combining advanced AI models with satellite data, public authorities, businesses and researchers can better address challenges such as climate change and emergency response.
Today’s satellites send enormous quantities of data down to Earth, crucial for applications ranging from fighting forest fires to navigating self-driving cars and monitoring climate change. Turning these raw data streams into usable intelligence requires advanced technological tools. That is where AI steps in.
AI powers space applications
‘By enabling everyday applications and improving the way we interact and obtain information and services, AI is redefining how users here on Earth use space technology and services’, said EUSPA Executive Director Rodrigo da Costa during the EUSPA AI Week in January 2026.
The latest EU Space Market Report, published by EUSPA in May 2026, also points to the rapid convergence of AI and space technologies. The report details how the global space downstream sector is expanding beyond traditional EO and Global Navigation Satellite System (GNSS) boundaries to incorporate emerging synergies, bolstering resilience, security and operational efficiency across numerous market segments.
According to the report, AI is becoming a core tool for interpreting satellite data. Within the space downstream domain, AI automates the interpretation of large volumes of imagery and sensor data for agricultural, environmental and infrastructure monitoring, as well as disaster management. It supports infrastructure predictive maintenance, improves maritime navigation and aids smart mobility solutions.
AI unlocks satellite intelligence
AI makes it possible for GNSS-enabled drone services to combine navigation, positioning, and data processing. In ports, combining EO imagery with GNSS-based tracking, AI, machine learning and data analytics can improve situational awareness and support cargo-security applications.
Moving from localised logistics and transport to broad planetary monitoring, the combined use of AI and space data scales up to tackle large-scale environmental threats. Consider the Copernicus constellation of satellites.
Equipped with powerful sensors looking at Earth, they generate dozens of terabytes of data every single day. The Horizon Europe-funded UNICORN consortium uses AI and Copernicus data to turn complex satellite observations into early-warning and forecasting tools for climate-related risks, including wildfire ignition. UNICORN’s researchers also developed a model that predicts how a fire might spread. This allows firefighters to identify areas with the highest potential to turn into major forest fires.
In addition to fire prevention, satellite data can also support climate mitigation. The EU-funded project SPACE4Cities developed software that estimates how much CO2 is being generated every hour in a city down to the level of individual housing blocks. Data from Sentinel-1 and Sentinel-2 satellites are used to do this. These data are fed into an AI model, together with available information from land-based sensors, to show CO2 emissions on the local level.
Satellite data can also monitor marine biodiversity and coastal water, preserving at-risk ecosystems. The EU-funded project ENHANCE engaged regional stakeholders in Spain and Greece being affected by the degradation and evolution of coastal marine ecosystems, to identify their needs and support effective decision making for sustainable climate-resilient coastal areas. Using AI algorithms, ENHANCE will deliver 3 new products to analyse the urban, agricultural and climate extremes pressures in coastal areas in Barcelona (Spain) and Pagasitikos Gulf (Greece).
Projects such as UNICORN and ENHANCE came together during the AI Week to exchange experiences and explore synergies between AI-driven space projects. They featured alongside initiatives such as ThinkingEarth, which uses AI to develop Copernicus foundation models, DaFab, an AI factory for Copernicus data at scale, and Embed2Scale, which develops the concept of EO embeddings and uses AI-based data compression to enable efficient exchange of EO and weather data.
Ultimately, AI is becoming indispensable for translating terabytes of orbital data into life-saving, practical insights for citizens, businesses and policymakers on the ground. EUSPA is helping accelerate this transformation by supporting AI-enabled applications built on Europe’s space programmes, including Copernicus, Galileo and EGNOS.
Media note: This feature can be republished without charge provided the European Union Agency for the Space Programme (EUSPA) is acknowledged as the source at the top or the bottom of the story. You must request permission before you use any of the photographs on the site. If you republish, we would be grateful if you could link back to the EUSPA website.