Harnessing Satellite Technology for Urban Energy Efficiency

Buildings account for nearly 40% of global energy consumption, so energy efficiency is a priority for governments, businesses and city planners. Finding the buildings that lose the most heat is hard. Traditional energy audits rely on manual inspections or drone surveys, which are expensive, slow and difficult to scale.

City governments need building-level thermal data to allocate funds and prioritise renovations. Construction firms and material suppliers need the same data to offer targeted energy-efficiency products. The project set out to build an automated, scalable way to map urban heat loss, supporting cost-efficient retrofitting and CO₂ reduction.

MELT-B (Monitoring, Estimating, and Simulating Loss of Thermal Energy in Buildings) combines Earth Observation data, artificial intelligence and geospatial analytics to map heat loss in office buildings. It processes high-resolution thermal imagery from space and joins it with building metadata such as energy class, footprint and materials. The result shows how each building performs and where energy-saving work will have the most effect.

Features include thermal heat maps for urban-scale analysis, building energy benchmarking to prioritise retrofits, CO₂ emission estimates and AI models that flag inefficient buildings. The project uses high-resolution satellite imagery such as SatVu, together with thermal drones, AI-based building segmentation and cloud processing for fast delivery at scale. Dashboards and API access let city planning tools and construction workflows use the data directly.

Initial pilot tests in Debrecen and Southampton identified buildings with high energy loss, validating the system's accuracy and scalability. MELT-B removes the need for expensive field surveys, so energy audits are faster and can cover a whole city. The platform produces data-driven renovation recommendations that help city planners target resources and track energy savings over time.