Giga's AI Satellite Mapping Reaches Every School in São Tomé and Príncipe

Sao Tome and Principe lacked a complete, reliable inventory of school locations, making it difficult for the Ministry of Education to plan and finance internet connectivity for classrooms. Giga -- the joint UNICEF-ITU initiative -- applies machine-learning models trained to recognise school buildings in high-resolution satellite imagery, then cross-references candidate sites against census data, OpenStreetMap and Overture Maps before local staff verify locations on the ground.

By February 2025, Giga reported that 100% of Sao Tome and Principe's basic and secondary schools had been mapped and validated, after which infrastructure modelling (cell towers, fibre routes) was used to give policymakers tools to plan and finance connectivity. IEEE Spectrum reported in December 2024 that this weakly-supervised deep-learning pipeline had by then mapped roughly a third of the world's schools across 141 countries.

Public documentation does not disaggregate accuracy figures or costs specifically for Sao Tome and Principe, and the practice addresses the infrastructure and administrative precursor to connectivity, not classroom teaching or learning outcomes directly.