Create README.md

README.md

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+---
+tags:
+  - renewable-energy
+  - geospatial
+  - satellite-imagery
+  - site-suitability
+  - olmoearth
+  - sentinel-2
+  - foundation-model
+  - embeddings
+license: mit
+task_categories:
+  - tabular-classification
+language:
+  - en
+size_categories:
+  - 10K<n<100K
+---
+
+# 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.
+
+## Links
+
+- GitHub: https://github.com/2imi9/O3earth
+- OlmoEarth: https://github.com/allenai/olmoearth_pretrain