Earth observation: From AI to Geo AI

For defence forces, in times of increased conflict, battlefield transparency and tactical intelligence are paramount. Satellite imagery is key for multi-domain operations, but the sheer volume and complexity of the data can overwhelm ISR (Intelligence, Surveillance, and Reconnaissance) teams. AI is a critical enabler, helping to automate the analysis of multi-source satellite imagery and extract key information for operations.

AI also scales up analytics for environmental monitoring, offering faster development, improved performance, and tailoring to customer needs. It can identify critical changes over time, helping to track deforestation, map land cover changes, study drought conditions, and monitor emission levels. As climate change accelerates, the need for near-real-time applications, anticipation, and fast responsiveness makes AI a crucial tool.

Following the initial waves of AI—machine learning and deep learning—we have now entered full speed in a new era with generative AI (genAI) and its core technologies such as Large Language Models (LLMs) and Foundation Models (FMs). Geospatial companies like Airbus, with our high-quality imagery, see genAI as a catalyst for a paradigm shift, transforming Earth observation into Earth exploration. This new era advocates for the democratisation of geospatial data, making it accessible to a broader community of end-users with no technical background required.

With a long-standing commitment to AI, Airbus has consistently pioneered the integration of artificial intelligence into its Earth observation products. such as our Pléiades Neo HD15 images. This product, derived from Pléiades Neo 30cm imagery, brightens colours and refines lines for improved readability and interpretation, all while maintaining the intrinsic qualities and precision of the original imagery. This technology can considerably improve the quality of insights derived from satellite data for decision-making in both defence and commercial applications.