--- license: - apache-2.0 # licenses vary per upstream Major TOM datasets (S2/S1/DEM/embeddings) language: - en tags: - remote-sensing - earth-observation - sentinel-2 - sentinel-1 - dem - embeddings - multimodal - deep-learning - taco pretty_name: Major TOM Core-Combo viewer: false ---
![Dataset Image](assets/taco.png)

This dataset follows the TACO specification.

# Major TOM Core-Combo (TACO) ![Dataset Image](assets/major_logo.png) 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. ## Description ### Dataset This dataset packages co-registered patches drawn 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 defines 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). ## Creators - ESA Φ-lab & collaborators ## Original datasets See the official **Major TOM** organization for coverage, counts and updates: - **Major TOM organization overview (Hugging Face)** - **Core datasets**: Core-S2L2A, Core-S2L1C, Core-S1RTC, Core-DEM - **Embedding releases**: Core-S2L1C-SSL4EO, Core-S1RTC-SSL4EO, Core-S2RGB-DINOv2, Core-S2RGB-SigLIP, Core-S2L1C-DeCUR, Core-S1RTC-DeCUR, Core-S2L2A-MMEarth, Core-AlphaEarth-Embeddings - **Spec & paper**: “Major TOM: Expandable Datasets for Earth Observation” (arXiv) and the IGARSS 2024 citation (see Publications) > Note: sizes/coverage and licenses are inherited from upstream. Always consult the upstream dataset cards. ## TACO dataset **Construction** - **Grid & tiling**: adopt Major TOM’s global grid; fixed-size **512 × 512 px @ 10 m** (~5.12 km) windows keyed by grid cell. - **Temporal pairing**: select closest-in-time S1/S2 acquisitions per cell (configurable), preferring **clear-sky** S2 for optical stacks. - **Embeddings**: if enabled, fetch and store per-patch embedding vectors (Parquet/NPY sidecar) indexed by the tortilla. - **Lineage metadata**: upstream identifiers/commits, acquisition timestamps, processing levels, and provenance. **Default patch geometry** - **Spatial extent**: 5160 m × 5160 m - **S2 tensor (bands)**: 13 (B1–B12 incl. B10) → **512 × 512 × 13** - **S1 tensor (VV/VH)**: 2 (plus optional angle) → **512 × 512 × 2–3** - **DEM tensor**: 1 (or +slope/aspect) → **512 × 512 × 1–3** - **Embeddings**: 1..N vectors stored as sidecars (per-patch, not per-pixel) ### 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 | --- ## 🔄 Reproducible Example ```python import tacoreader import rasterio as rio import numpy as np import matplotlib.pyplot as plt # Load the dataset (replace with the final registry name when published) ds = tacoreader.load("tacofoundation:majortom-core-combo") # Read a sample i = 0 row = ds.read(i) row_id = ds.iloc[i]["tortilla:id"] s2_path = row.read("S2_L2A") # GeoTIFF s1_path = row.read("S1_RTC") # GeoTIFF dem_path = row.read("DEM") # GeoTIFF # emb_path = row.read("EMB") # Optional embeddings (Parquet/NPY) with rio.open(s2_path) as s2, rio.open(s1_path) as s1, rio.open(dem_path) as dem: # Simple S2 RGB (B4,B3,B2) rgb = np.stack([s2.read(4), s2.read(3), s2.read(2)], axis=0) rgb = np.transpose(rgb, (1,2,0)) rgb_norm = np.clip(rgb / 2000.0, 0, 1) vv = s1.read(1) dem_elev = dem.read(1) fig, ax = plt.subplots(1,3, figsize=(13,4.2)) ax[0].imshow(rgb_norm); ax[0].set_title(f"S2 RGB — {row_id}"); ax[0].axis("off") ax[1].imshow(vv); ax[1].set_title("S1 VV"); ax[1].axis("off") ax[2].imshow(dem_elev); ax[2].set_title("DEM"); ax[2].axis("off") plt.tight_layout(); plt.show() ```
example
## 🛰️ Sensor Information Sources in this dataset: **sentinel2msi**, **sentinel1-rtc**, **cop-dem30**, and **Major TOM embeddings** (SSL4EO, DINOv2, SigLIP, DeCUR, MMEarth; optional AlphaEarth). ## 🎯 Tasks General-purpose: **self-supervised pretraining**, **representation learning**, **multimodal fusion**, **semantic segmentation**, **change detection**, **classification**, **retrieval**. ## 📂 Original Data Repositories (Upstream) * Major TOM organization [page](https://huggingface.co/Major-TOM). ## 💬 Discussion Use the Major TOM org discussions/Spaces and the **satellite-image-deep-learning Discord** (Major TOM channels) to coordinate contributions and combinations. ## 🔀 Split Strategy All train. ## 📚 Scientific Publications ### Publication 01 * **arXiv**: *Major TOM: Expandable Datasets for Earth Observation* (Francis & Czerkawski, 2024). **BibTeX**: ```bibtex @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} } ``` ### Publication 02 * **arXiv (2024)**: *Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space*. ```bibtex @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{\"A} and others}, journal={arXiv preprint arXiv:2412.05600}, year={2024}, doi= {10.48550/arXiv.2412.05600} } ``` ## 🤝 Data Providers | **Name** | **Role** | **URL** | | :---------------------------- | :--------------------- | :------------------------------------------------------------------- | | ESA Φ-lab | producer / coordinator | [https://philab.esa.int/](https://philab.esa.int/) | | Major TOM (HF) | publisher (org) | [https://huggingface.co/Major-TOM](https://huggingface.co/Major-TOM) | | CloudFerro (embeddings infra) | collaborator | [https://cloudferro.com/](https://cloudferro.com/) | --- ## 🧑‍🔬 Curators | **Name** | **Organization** | **URL** | | :-------------- | :------------------------ | :------------------------------------------------------------------------------------------------- | | Julio Contreras | Image & Signal Processing | [https://juliocontrerash.github.io/](https://juliocontrerash.github.io/) | | TACO Foundation | Curation (TACO format) | [https://huggingface.co/datasets/tacofoundation/](https://huggingface.co/datasets/tacofoundation/) | --- ## 🎞 Official Image Datasets (from Major TOM) | Dataset | Modality | Number of Patches | Sensing Type | Comments | | ---------- | ------------------- | ----------------- | --------------------- | --------------- | | Core-S2L2A | Sentinel-2 Level 2A | 2,245,886 | Multi-Spectral | Global (≈23 TB) | | Core-S2L1C | Sentinel-2 Level 1C | 2,245,886 | Multi-Spectral | Global (≈23 TB) | | Core-S1RTC | Sentinel-1 RTC | 1,469,955 | SAR | Global (≈16 TB) | | Core-DEM | Copernicus DEM 30 | 1,837,843 | Digital Surface Model | Global (≈1 TB) | --- ## 📊 Official Embedding Datasets (from Major TOM) | Dataset | Modality | # Embeddings | Sensing Type | Source Dataset | Source Model | Size | | -------------------------- | -------------------- | -------------- | -------------- | -------------- | --------------------- | -------- | | Core-S2L1C-SSL4EO | Sentinel-2 Level 1C | 56,147,150 | Multi-Spectral | Core-S2L1C | SSL4EO-ResNet50-DINO | 252.9 GB | | Core-S1RTC-SSL4EO | Sentinel-1 RTC | 36,748,875 | SAR | Core-S1RTC | SSL4EO-ResNet50-MOCO | 332.5 GB | | Core-S2RGB-DINOv2 | Sentinel-2 L2A (RGB) | 56,147,150 | True Colour | Core-S2L2A | DINOv2 | 223.1 GB | | Core-S2RGB-SigLIP | Sentinel-2 L2A (RGB) | 20,212,974 | True Colour | Core-S2L2A | SigLIP-SO400M-384 | 41.3 GB | | Core-S2L1C-DeCUR | Sentinel-2 Level 1C | 56,147,150 | Multi-Spectral | Core-S2L1C | SSL4EO-ResNet50-DeCUR | 252.9 GB | | Core-S1RTC-DeCUR | Sentinel-1 RTC | 36,748,875 | SAR | Core-S1RTC | SSL4EO-ResNet50-DeCUR | 332.5 GB | | Core-S2L2A-MMEarth | Sentinel-2 L2A (MSI) | 39,727,477,454 | Multi-Spectral | Core-S2L2A | MMEarth | 5080 GB | | Core-AlphaEarth-Embeddings | Multimodal | 71,276,453,136 | Multiple | AlphaEarth | AlphaEarth | 6070 GB | --- **Key sources for facts & tables:** Major TOM org page with official tables and IGARSS citation (org card), the arXiv paper describing the framework and grid, specific upstream dataset cards (Core-S2L2A / Core-S1RTC / Core-DEM), the AlphaEarth subset card, and ESA Φ-lab’s post on embedding expansions. ([huggingface.co][1], [arxiv.org][2], [philab.esa.int][3]) [1]: https://huggingface.co/Major-TOM "Major-TOM (Major TOM)" [2]: https://arxiv.org/abs/2402.12095 "Major TOM: Expandable Datasets for Earth Observation" [3]: https://philab.esa.int/new-ai-powered-insights-with-the-latest-major-tom-embeddings/ "New AI-powered insights with the latest Major TOM embeddings"