| { |
| "model_name": "AlphaEarthFoundations", |
| "model_type": "alphaearthfoundations", |
| "architectures": [ |
| "AlphaEarthFoundations", |
| "STPBlock", |
| "ConditionalDecoder" |
| ], |
| "framework": "PyTorch", |
| "domain": "earth-observation", |
| "task": "multi-source-geospatial-embedding", |
| "implementation": { |
| "entry_point": "model/alphaearthfoundations.py", |
| "scope": "engineering reproduction of a multi-source spatiotemporal embedding field for sparse-label global Earth observation mapping", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "architecture": { |
| "family": "spatiotemporal precision-time-space embedding field", |
| "input_sources": [ |
| "sentinel2", |
| "sentinel1", |
| "landsat" |
| ], |
| "precision_dim": 8, |
| "time_dim": 16, |
| "space_dim": 32, |
| "embedding_dim": 64, |
| "num_blocks": 1, |
| "num_heads": 4, |
| "decoder_hidden_dim": 32, |
| "vmf_kappa": 8000.0, |
| "max_geometry_dim": 2, |
| "embedding_normalization": "L2 unit sphere", |
| "paper_model": { |
| "precision_dim": 128, |
| "time_dim": 512, |
| "space_dim": 1024, |
| "embedding_dim": 64, |
| "num_blocks": 15, |
| "parameter_count": "approximately 480M" |
| } |
| }, |
| "data": { |
| "datasets": [ |
| "Google Satellite Embedding V1 Annual" |
| ], |
| "protocol": "aef_synthetic_paper_spec_v3", |
| "format": "NPZ", |
| "train_file": "data/train.npz", |
| "test_file": "data/test.npz", |
| "image_size": 128, |
| "spatial_extent_km": [ |
| 1.28, |
| 1.28 |
| ], |
| "grid_resolution_m": 10, |
| "input_sources": { |
| "sentinel2": { |
| "timesteps": 65, |
| "channels": 5, |
| "geometry_dim": 0 |
| }, |
| "sentinel1": { |
| "timesteps": 17, |
| "channels": 5, |
| "geometry_dim": 2 |
| }, |
| "landsat": { |
| "timesteps": 21, |
| "channels": 7, |
| "geometry_dim": 0 |
| } |
| }, |
| "target_sources": { |
| "sentinel2": {"channels": 5, "type": "continuous", "loss_grid_m": 10}, |
| "sentinel1": {"channels": 5, "type": "continuous", "loss_grid_m": 10}, |
| "landsat": {"channels": 7, "type": "continuous", "loss_grid_m": 30}, |
| "palsar2": {"channels": 3, "type": "continuous", "loss_grid_m": 30}, |
| "era5_land": {"channels": 12, "type": "continuous", "loss_grid_m": 10}, |
| "gedi": {"channels": 101, "type": "continuous", "loss_grid_m": 20}, |
| "grace": {"channels": 1, "type": "continuous", "loss_grid_m": 1280}, |
| "glo30": {"channels": 1, "type": "continuous", "loss_grid_m": 30}, |
| "nlcd": {"channels": 16, "type": "categorical", "loss_grid_m": 30} |
| }, |
| "required_metadata": [ |
| "format_version", |
| "data_source", |
| "timestamps", |
| "frame_available", |
| "channel_available", |
| "pixel_valid", |
| "geometry", |
| "support_period", |
| "valid_period", |
| "text_target" |
| ] |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/alphaearthfoundations.py", |
| "scripts/fake_data.py", |
| "scripts/train.py", |
| "scripts/inference.py", |
| "scripts/result.py" |
| ] |
| } |
|
|
