According to AI at Meta, Meta announced Canopy Height Maps v2 (CHMv2), an open source model for high‑resolution global forest canopy mapping built with the World Resources Institute, leveraging the DINOv3 Sat-L vision model optimized for satellite imagery to improve canopy height estimation accuracy and coverage. As reported by AI at Meta, CHMv2 enables near-global inference from multispectral satellite data, offering finer spatial resolution for forestry monitoring, biomass estimation, and carbon accounting use cases. According to AI at Meta, the open release lowers costs for governments, NGOs, and climate tech startups to integrate canopy height layers into geospatial AI pipelines for MRV (measurement, reporting, and verification) and nature-based solutions.

According to AI at Meta on X, Meta has open sourced CHMv2, a global canopy height model already supporting public sector programs in the United States and Europe to inform carbon offsetting, reforestation, and land management decisions; the announcement directs readers to the research paper for technical details. As reported by AI at Meta, making CHMv2 openly available is intended to accelerate remote sensing research and improve monitoring workflows for forestry and climate agencies. According to AI at Meta, the model’s public release creates opportunities for AI developers and geospatial firms to integrate canopy metrics into MRV systems, climate risk analytics, and nature-based solutions marketplaces.