Require satellite evidence for energy and AI data center approvals, researchers urge governments
Satellite data could help governments decide where to build the data centres behind the growth of AI, by showing where renewable power, water and land are available and where drought and climate risks are highest, according to researchers at the University of Surrey.
Writing in Nature Reviews Clean Technology, the team argues that Earth observation (information about the planet's systems gathered largely by satellites), which is often underused, should become a formal part of how governments, regulators and investors plan, run and check the clean energy transition.
The call from Surrey researchers comes as demand floods the queue to connect to Britain's electricity grid. According to Ofgem, contracted demand in that queue rose from 41 gigawatts to 125 gigawatts between November 2024 and June 2025, driven largely by data centre projects.
Globally, the International Energy Agency expects electricity use by data centres to double from 485 terawatt-hours in 2025 to 950 terawatt-hours by 2030, roughly the amount of electricity Japan uses in a year.
The authors say geospatial and satellite data can support more strategic data centre planning by combining information on renewable energy potential, land-surface temperature, open water and groundwater availability, drought exposure, biodiversity, land-use constraints and climate-risk projections.
Dr Ana Andries, Senior Lecturer in GIS, Remote Sensing and Environmental Assessment and lead author of the Comment from the University of Surrey, said:
"Every new data centre is a long-term decision about power, water and land, while also an increasing source of global carbon emissions. Satellites already give us detailed and regularly updated information on all three, yet that evidence is too often left out of the decisions that matter. We're asking governments to write it into the rules, so the infrastructure behind the AI boom goes where the grid, renewable energy potential and the landscape can support it."
The Comment also sets out how satellites and related geospatial data support planning, operation and monitoring. For planning, the Global Solar Atlas uses satellite data to map solar power potential worldwide, while MapYourGrid, an open-source community project, is mapping power lines, substations and power plants so planners can see where new generation can connect. Once infrastructure is running, thermal imaging from space could help identify faults such as hot spots on solar panels, while radar from Sentinel-1 satellites can map wind at the sea surface around offshore wind farms, including the slower air in the wakes the farms leave behind.
Water is one area where energy systems are exposed. For instance, this summer's drought pushed the Danube to record lows and forced Romania to shut down both reactors at the Cernavodă nuclear plant, which normally supplies about a fifth of the country's electricity. Climate data and satellite monitoring of river levels, reservoirs and drought can help estimate risks to hydropower and to power stations that rely on river water for cooling, and help protect a dispatchable electricity supply. For accountability, some methane-sensing satellites detected releases as small as 0.03 tonnes per hour in single-blind controlled tests, though performance varied between systems. This gives regulators a way to check emissions from oil and gas infrastructure. Satellite imagery has also been used to map mining expansion linked to clean-energy supply chains in the Democratic Republic of Congo.
The authors call on governments and regulators to require satellite evidence in renewable energy zoning, infrastructure permitting, climate-risk screening and environmental impact assessment, especially where projects affect land, water, biodiversity or grid access. Energy plans and regulatory reporting should also set out clear data standards, validation requirements and how uncertainty is reported. For investors and utilities, they argue, satellite data should become part of due diligence and asset-risk assessment. Satellite data should support these decisions, they add, not replace ground data, local knowledge or official reporting.
Delivering this will need capacity building, the authors say – energy ministries, regulators, utilities, local authorities and investors need trusted satellite products, practical guidance, standards, training and evidence that the approach is cost-effective.
Professor Ravi Silva, Distinguished Professor and Director of the Advanced Technology Institute at the University of Surrey and co-author of the Comment, said:
"Building a clean energy future requires thousands of decisions, from choosing locations for solar farms, wind turbines, transmission infrastructure and energy storage to ensuring these assets operate effectively over their lifetime. Better evidence helps make these decisions more efficient, cost-effective and reliable. Satellite data can help identify areas with strong solar and wind resources, map existing infrastructure, detect operational issues, and provide independent information to support monitoring and oversight."
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Notes to editors
Citation: Andries, A., Xuan, J., Liu, L. et al. Leverage Earth observation data to support the clean energy transition. Nat. Rev. Clean Technol. (2026). https://doi.org/10.1038/s44359-026-00220-y
Journal
Nature Reviews Clean Technology
Article Title
Leverage Earth observation data to support the clean energy transition
Learning maths goes (slightly) better with AI, but teacher plays a key role
Primary school pupils who use an AI-supported learning tool learn arithmetic more quickly than children who do not use such a tool
Radboud University Nijmegen
Primary school pupils who use an AI-supported learning tool learn arithmetic more quickly than children who do not use such a tool. This is the finding of a multi-year study by Radboud University involving nearly eight thousand children. However, the researchers warn that it's no miracle cure, as the teacher’s role remains essential even with AI.
The researchers examined the development of numeracy skills among 7,885 Dutch primary school pupils over a three-year period, when these systems were first used between 2014 and 2017. They compared classes that used an adaptive learning system with classes that taught numeracy without such a system. Such a system automatically adapts exercises to the level of an individual pupil. Pupils are given more difficult tasks if they perform well and simpler tasks if they get stuck. On average, pupils who used the system showed more positive growth in their maths performance over the years.
Large-scale study
‘It is one of the first studies to examine the long-term effects of adaptive learning tools. Until now, research into these kinds of systems has mainly focused on short-term effects, or has been conducted on a smaller scale,’ explains Susanne de Mooij, an education researcher and one of the study’s authors.
‘Adaptive learning systems have been in use for almost fifteen years in more than half of all Dutch primary schools. Nevertheless, some fear that this type of adaptive learning tool leads to pupils learning less effectively, as digital learning materials are thought to be less effective than paper-based ones. This study shows that, in cognitive terms at least, this is not the case.’
Greater success at large schools
The effects found are modest, De Mooij emphasises. ‘We have found small effects, but generally a positive trend. Moreover, the positive effect is particularly evident in large schools and in vulnerable schools with many pupils from less advantaged socio-economic backgrounds. There is often greater variation between pupils in such settings. Adaptive technology can then help to better tailor teaching to individual needs,’ says De Mooij.
This means that an adaptive learning tool is primarily something that supports teachers, rather than replacing them. ‘A teacher cannot adapt the lesson content to thirty pupils at the same time. But with a tool like this, you can improve pupils’ maths skills whilst also reducing a teacher’s workload.’ The researchers emphasise that the teacher always remains in control: ‘The teacher draws up the lesson plan, decides what pupils learn and oversees what happens in the classroom. Such learning technology is fed solely by the data stored in the system, whereas a teacher has access to much more information.’
Journal
Learning and Instruction
Article Title
Arithmetic development: a longitudinal observational study into the use of adaptive technology
Article Publication Date
1-Oct-2026
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