Most nations are sitting on an unmapped archaeological estate. Crop-marks, soil anomalies, buried walls and ancient field systems are invisible to ground survey teams but readable from orbit — provided you have the right sensors and the expertise to interpret them. Countries that rely on commercial tasking services to prospect their own territory are, in practice, outsourcing decisions about what gets found, when it gets looked at, and who holds the raw data. That is an untenable position for any state that regards its pre-colonial or pre-modern heritage as a sovereign asset.
A purpose-built constellation delivers the three data types that drive prospection: high-resolution multispectral imagery revealing crop-marks and soil-moisture differentials (30 cm–3 m GSD), L-band or P-band SAR penetrating dry-sand environments to expose buried mud-brick or stone structures, and thermal IR capturing diurnal heat-retention differences over buried masonry. Repeat passes timed to the agricultural calendar — ploughing, growing and harvest seasons each expose different signatures — produce far more leads per hectare than any single acquisition. Machine-learning pipelines trained on excavated ground-truth then rank anomalies so field teams chase real targets, not noise.
The operational outcome is a continuously updated national prospection database: a ranked inventory of candidate sites that feeds environmental-impact assessment, development planning decisions, and research excavation programmes. Countries that have run even partial satellite prospection campaigns — Egypt's alluvial plain, Bolivia's Llanos de Mojos, Cambodia's Greater Angkor hinterland — have doubled or tripled the count of known sites within months. Owning the tasking cadence and the archive means that data is available for every future analysis, not just the one a commercial vendor agreed to sell.