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granite-geospatial-canopyheight

Hugging Face model ibm-granite/granite-geospatial-canopyheight (image-feature-extraction)

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What's in it

Data offered docs-verified
canopy height (tree and vegetation height) prediction from HLS L30 optical imagery
Coverage docs-verified
Global (fine-tuned across 15 biomes)
Resolution llm-inferred
30 m (inferred from the HLS L30 product name)
Formats docs-verified
PyTorch checkpoint (pytorch_model.bin) · YAML model config (config.yaml)
Access docs-verified
Free and open source, Apache-2.0 licence; weights downloaded from Hugging Face and run locally with TerraTorch

Useful for

Use cases llm-inferred
Canopy height baseline for carbon sequestration estimates of nature-based solutions · Vegetation and woodland height context for ecological habitat surveys · Regional canopy height screening for timber or crop-yield assessments
Audience llm-inferred
ecologists · GIS analysts · remote sensing specialists · environmental consultants · hydrologists (land-cover context)

Limitations

Constraints llm-inferred
Optical imagery only (HLS L30); no SAR or LiDAR inputs · Requires cloud-free composite imagery of the area as input · Docs cite GEDI L2A in the summary but GEDI L4A in Training Data; the label source is inconsistent · Training uses sparse GEDI labels, so accuracy outside the training biomes is not stated · No UK-specific validation is stated in the docs · Requires a Python environment with TerraTorch; no GUI · Single release (tag v1, 04/11/2024); no update cadence stated · IBM states it will not maintain this code going forward, so upkeep risk is high
Licence
apache-2.0
Authentication
No API key required (repository README, auto-extracted; check upstream requirements)
GitHub stars
Unknown
Last commit
Unknown
Last successful page check
14/10/2026
Page health
healthy
Package
Not recorded
Verification
Not independently verified

Provenance & evidence

Verified 2026-10-15 via HF API: exists; 14 downloads/30d, 19 likes.

Metadata observed 14/10/2026 · research sweep: manual-2026-10-15 (Hugging Face models)