Global and Regional High-Resolution Canopy Height Maps from Satellite Imagery

Global and regional canopy height maps created by WRI and Meta. The maps were generated using machine learning models applied to high-resolution Maxar satellite imagery. The dataset is licensed under CC-BY-4.0.

Use Cases

• Modeling forest carbon stocks based on canopy height estimates.
• Monitoring deforestation and forest degradation over time using canopy height changes.
• Assessing biodiversity and habitat structure based on canopy height variability.
• Calibrating or validating other land cover or biomass datasets using high-resolution canopy data.

Strengths

• Derived from high-resolution worldwide Maxar satellite imagery.
• Created using machine learning models, suggesting a data-driven methodology.
• License is explicitly stated as CC-BY-4.0, permitting broad reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.
• Row count and file size are unknown, which may limit suitability assessment.

Provenance

Source

Meta and World Resources Institute (WRI).

Collection Method

Created using machine learning models on high-resolution Maxar satellite imagery.

Time Range

Temporal coverage is not specified in the input.

Freshness

Last updated date is unknown.

Geography

Global and regional coverage.