|
|
description = """ |
|
|
## Description |
|
|
|
|
|
### Dataset |
|
|
|
|
|
A TACO-formatted multimodal dataset built on **Major TOM**. Each sample aligns **Sentinel-2 L2A**, **Sentinel-1 RTC**, **Copernicus DEM 30**, and optional **Major TOM embeddings** under a single grid so patches are spatially matched and ready for training and evaluation. |
|
|
|
|
|
This dataset assembles co-registered patches from the **Major TOM core datasets** (S2 L2A / S2 L1C / S1 RTC / DEM) and the official **Major TOM embeddings** (SSL4EO, DINOv2, SigLIP, DeCUR, MMEarth, AlphaEarth). Major TOM provides a **geographical indexing grid** and a **metadata structure** to merge multi-source EO data—ideal for large-scale pretraining, representation learning, and multimodal fusion. |
|
|
|
|
|
**What each sample contains:** |
|
|
- **S2 L2A (10 m)** — 13 MSI bands (B1–B12 incl. B10), with native 20 m/60 m bands resampled to 10 m for a consistent stack. |
|
|
- **S1 RTC (10 m)** — backscatter (VV/VH) and optional geometry/angle layers, co-registered to the S2 grid. |
|
|
- **DEM (30 m → 10 m)** — Copernicus DEM 30 resampled to 10 m, with optional derived slope/aspect. |
|
|
- **Embeddings (optional)** — one or more per-patch vectors from Major TOM families (e.g., SSL4EO, DINOv2, SigLIP, DeCUR, MMEarth, AlphaEarth). |
|
|
- **Metadata** — acquisition dates, orbit/pass, QA (e.g., S2 cloud metrics when available), CRS and affine transform, plus upstream lineage. |
|
|
|
|
|
The dataset inherits **global land coverage** from Major TOM Core and is **extensible** (you can enable/disable modalities and embeddings per tortilla). |
|
|
|
|
|
### Sensors used |
|
|
|
|
|
- **Sentinel-2 MSI (L2A/L1C)** — optical multispectral, 13 bands (443–2190 nm) at 10/20/60 m; all represented on a unified 10 m grid. |
|
|
- **Sentinel-1 RTC** — SAR backscatter (VV/VH) in analysis-ready RTC format at ~10 m. |
|
|
- **Copernicus DEM 30** — global 30 m elevation resampled to 10 m for alignment. |
|
|
- **Embeddings** — model-derived features aligned to the same grid (families: SSL4EO, DINOv2, SigLIP, DeCUR, MMEarth; optional AlphaEarth subset). |
|
|
|
|
|
### Spectral Bands (S2 MSI) |
|
|
|
|
|
We expose the native Sentinel-2 MSI band set and place all on a unified 10 m grid: |
|
|
|
|
|
| idx | Band | Name | Central λ | Nominal Res. | Notes | |
|
|
|:---:|:----:|---------------------------|:---------:|:------------:|------| |
|
|
| 0 | B1 | Coastal Aerosol | 443 nm | 60 m | resampled to 10 m | |
|
|
| 1 | B2 | Blue | 492 nm | 10 m | | |
|
|
| 2 | B3 | Green | 560 nm | 10 m | | |
|
|
| 3 | B4 | Red | 665 nm | 10 m | | |
|
|
| 4 | B5 | Red Edge 1 | 704 nm | 20 m | resampled to 10 m | |
|
|
| 5 | B6 | Red Edge 2 | 740 nm | 20 m | resampled to 10 m | |
|
|
| 6 | B7 | Red Edge 3 | 783 nm | 20 m | resampled to 10 m | |
|
|
| 7 | B8 | NIR (Broad) | 833 nm | 10 m | | |
|
|
| 8 | B8A | NIR (Narrow) | 865 nm | 20 m | resampled to 10 m | |
|
|
| 9 | B9 | Water Vapour | 945 nm | 60 m | resampled to 10 m | |
|
|
| 10 | B10 | Cirrus (WV 1375 nm) | 1375 nm | 60 m | optional for ML | |
|
|
| 11 | B11 | SWIR 1 | 1610 nm | 20 m | resampled to 10 m | |
|
|
| 12 | B12 | SWIR 2 | 2200 nm | 20 m | resampled to 10 m | |
|
|
""" |
|
|
|
|
|
bibtex_1 = """ |
|
|
@article{MajorTOM2024, |
|
|
author = {Francis, Alistair and Czerkawski, Mikolaj}, |
|
|
title = {Major TOM: Expandable Datasets for Earth Observation}, |
|
|
journal = {arXiv preprint arXiv:2402.12095}, |
|
|
year = {2024}, |
|
|
doi = {10.1109/IGARSS53475.2024.10640760} |
|
|
} |
|
|
""" |
|
|
|
|
|
|
|
|
bibtex_2 = """ |
|
|
@article{czerkawski2024global, |
|
|
title = {Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space}, |
|
|
author = {Czerkawski, Mikolaj and Kluczek, Marcin and Bojanowski, J. and others}, |
|
|
journal = {arXiv preprint arXiv:2412.05600}, |
|
|
year = {2024}, |
|
|
doi = {10.48550/arXiv.2412.05600} |
|
|
} |
|
|
""" |
|
|
|
|
|
|
|
|
collection_object = tacotoolbox.datamodel.Collection( |
|
|
id="majortom-core-combo", |
|
|
title="Major TOM Core-Combo (TACO)", |
|
|
dataset_version="1.0.0", |
|
|
description=description, |
|
|
licenses=["refer-to-upstream"], |
|
|
extent={ |
|
|
"spatial": [[-180.0, -90.0, 180.0, 90.0]], |
|
|
"temporal": [["2014-01-01T00:00:00Z", "2025-09-09T00:00:00Z"]] |
|
|
}, |
|
|
providers=[ |
|
|
{ |
|
|
"name": "ESA Φ-lab / Major TOM (Hugging Face)", |
|
|
"roles": ["producer", "publisher"], |
|
|
"links": [ |
|
|
{"href": "https://huggingface.co/Major-TOM", "rel": "source", "type": "text/html"} |
|
|
], |
|
|
}, |
|
|
{ |
|
|
"name": "TACO Foundation", |
|
|
"roles": ["curator"], |
|
|
"links": [ |
|
|
{"href": "https://huggingface.co/datasets/tacofoundation/", "rel": "homepage", "type": "text/html"} |
|
|
], |
|
|
} |
|
|
], |
|
|
keywords=["remote-sensing", "earth-observation", "multimodal", "deep-learning", |
|
|
"sentinel-2", "sentinel-1", "dem", "embeddings", "taco"], |
|
|
task="multimodal-learning", |
|
|
curators=[ |
|
|
{ |
|
|
"name": "Julio Contreras", |
|
|
"organization": "Image & Signal Processing", |
|
|
"email": ["[email protected]"], |
|
|
"links": [{"href": "https://juliocontrerash.github.io/", "rel": "homepage", "type": "text/html"}], |
|
|
}, |
|
|
{ |
|
|
"name": "TACO Foundation", |
|
|
"organization": "TACO", |
|
|
"links": [{"href": "https://huggingface.co/datasets/tacofoundation/", "rel": "homepage", "type": "text/html"}], |
|
|
} |
|
|
], |
|
|
split_strategy="all-train", |
|
|
discuss_link={ |
|
|
"href": "https://huggingface.co/Major-TOM", |
|
|
"rel": "discussion", |
|
|
"type": "text/html" |
|
|
}, |
|
|
raw_link={ |
|
|
"href": "https://huggingface.co/Major-TOM", |
|
|
"rel": "source", |
|
|
"type": "text/html" |
|
|
}, |
|
|
|
|
|
optical_data={"sensor": "sentinel2msi"}, |
|
|
radar_data={"sensor": "sentinel1-rtc"}, |
|
|
elevation_data={"sensor": "cop-dem30"}, |
|
|
embeddings={ |
|
|
"families": ["SSL4EO", "DINOv2", "SigLIP", "DeCUR", "MMEarth", "AlphaEarth"], |
|
|
"storage": "per-patch vectors (Parquet/NPY sidecars)" |
|
|
}, |
|
|
taco_spec={ |
|
|
"grid": "Major TOM global grid", |
|
|
"patch_size_px": [512, 512], |
|
|
"resolution_m": 10, |
|
|
"spatial_extent_m": [5160, 5160], |
|
|
"assets": { |
|
|
"S2_L2A": "GeoTIFF, 13 bands (B1–B12 incl. B10) @10m", |
|
|
"S1_RTC": "GeoTIFF, 2–3 bands (VV, VH, optional angle) @10m", |
|
|
"DEM": "GeoTIFF, 1–3 bands (elevation, optional slope/aspect) @10m", |
|
|
"EMB": "Optional per-patch embeddings (Parquet/NPY)" |
|
|
} |
|
|
}, |
|
|
labels={ |
|
|
"label_classes": [], |
|
|
"label_description": "No labeled classes. Designed for representation learning and multimodal tasks." |
|
|
}, |
|
|
scientific={ |
|
|
"doi": "to-be-assigned", |
|
|
"citation": "Please cite the Major TOM paper(s) and the IGARSS 2024 proceeding.", |
|
|
"summary": "Major TOM Core-Combo reorganizes upstream Major TOM sources (S2/S1/DEM and embeddings) into aligned TACO tortillas for fast, consistent access.", |
|
|
"publications": [ |
|
|
{"doi": "10.48550/arXiv.2402.12095", "citation": bibtex_1, "summary": "arXiv paper introducing the Major TOM framework."}, |
|
|
{"doi": "10.48550/arXiv.2412.05600", "citation": bibtex_2, "summary": "arXiv on global/dense embeddings aligned to Major TOM grid."} |
|
|
] |
|
|
} |
|
|
) |
|
|
|
