Foundation models for Earth observation and geospatial.

Technologies

• EO foundation models Large pretrained models over optical, SAR and multi-temporal imagery, fine-tuned for many downstream tasks.
• Training data and labels Documented, licensed training sets with known label quality and geographic coverage.
• Land cover and change detection Classification and change maps with accuracy reported against reference data.
• Hazard and exposure mapping Flood, fire, landslide and subsidence mapping that feeds risk and response decisions.
• SAR interferometry and deformation analysis Measuring millimetre ground and structure movement from radar phase, with learned noise and unwrapping aids.
• Geospatial embeddings and similarity search Vector representations of places and scenes that make large archives searchable by example.
• Super-resolution and gap filling Generative methods that sharpen or fill imagery, labelled as model output with stated uncertainty.
• AI weather and climate emulators Learned models that emulate numerical weather prediction at much lower compute cost.
• Geospatial model metadata Machine-readable model descriptions with inputs, bands, resolution and intended use.