For years, verifying restoration outcomes across remote African landscapes meant costly, infrequent field visits — leaving long gaps where degradation or project failure could go unnoticed.
VIA Foundation's monitoring and verification team has built a framework that layers satellite imagery, machine-learning canopy analysis, and community-reported field data into a single dashboard updated monthly across all active project sites.
The system flags underperforming plots automatically, letting field teams intervene early rather than discovering a failed planting a year later — and gives funders real-time, independently verifiable confidence in reported outcomes.