Global Canopy Height Maps Derived from Satellite Imagery

Version 2 global and regional canopy height maps were created using machine learning models on high-resolution Vantor satellite imagery. The dataset is produced by Meta in collaboration with the World Resources Institute. The temporal coverage and resolution specifics are not provided.

Use Cases

• Modeling above-ground biomass by analyzing canopy height values across different forest regions.
• Monitoring deforestation and forest degradation over time by comparing canopy height map versions.
• Calibrating airborne LiDAR surveys using the satellite-derived canopy height data as a baseline.
• Studying the relationship between canopy height and biodiversity indicators in specific ecological zones.

Strengths

• Global coverage provides a consistent view of forest structure.
• Derived from high-resolution Vantor satellite imagery.
• Uses machine learning models for data generation.
• Released as Version 2, indicating iterative improvement.

Limitations

• Sample data, row count, and specific spatial/temporal resolution are unknown.
• Accuracy of the machine learning models relative to ground truth is not specified.
• Potential for cloud cover or atmospheric artifacts in the source satellite imagery.

Provenance

Source

Meta, in collaboration with the World Resources Institute (WRI).

Collection Method

Created using machine learning models applied to Vantor satellite imagery.

Time Range

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Freshness

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Geography

Global and regional coverage.