Datasets:

2imi9
/

O3earth

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O3 EartH Dataset

Geospatial site suitability dataset with OlmoEarth foundation model embeddings for renewable energy infrastructure assessment.

Key result: OlmoEarth embeddings achieve AUC 0.867 under spatial cross-validation (leave-one-country-out).

Files

File	Description
suitability_dataset_v2_shuffled.parquet	24,866 labeled samples (lat, lon, energy_type, label, country)
all_energy_locations.parquet	321,614 global energy plant locations from EIA + OSM
embeddings/embeddings.npy	8,000 OlmoEarth 768-dim embeddings
embeddings/embeddings_meta.csv	Metadata for each embedding
models/xgb_*.json	Trained XGBoost classifiers per energy type
models/scaler_*.pkl	StandardScaler for each energy type

How Embeddings Were Extracted

Sentinel-2 L2A (12 bands, 10m resolution) patches are passed through frozen OlmoEarth BASE encoder (97M params), then mean-pooled to produce a 768-dimensional landscape fingerprint per location.

Source imagery: Microsoft Planetary Computer
Model: allenai/olmoearth_pretrain (OLMOEARTH_V1_BASE)
Patch size: 128x128 pixels (~1.28km)
Time range: 2022-2023, max 30% cloud cover

Coverage

100+ countries across 6 continents
4 energy types: solar (10K), wind (10K), hydro (4K), geothermal (866)
Balanced positive (existing sites) and negative (random locations) samples

Results

Method	AUC
Geography only (lat/lon)	0.579
OlmoEarth embeddings	0.902
Spatial CV (leave-one-country-out)	0.867

Citation

Qi, Ziming. "O3 EartH: Geospatial Site Suitability Assessment Using Foundation Model Embeddings." 2026. Northeastern University.