Upload: Complete folder into assets directory

README.md

@@ -0,0 +1,265 @@
+---
+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
+---
+
+<div style="text-align: center; border: 1px solid #ddd; border-radius: 10px; padding: 15px; max-width: 260px; margin: auto; background-color: #f9f9f9;">
+  
+
+![Dataset Image](assets/taco.png)
+
+<b><p>This dataset follows the TACO specification.</p></b>
+
+</div>
+
+<br>
+
+# 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()
+```
+
+<center>
+  <img src="assets/majortom_combo_example.png" alt="example" width="100%"/>
+</center>
+
+## 🛰️ 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"

collection.py

@@ -0,0 +1,155 @@
+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}
+}
+"""
+
+# Create a collection object with metadata for the dataset
+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]],  # global coverage (land-focused per upstream)
+        "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"
+    },
+    # Optional domain-specific metadata (mirrors your README sections)
+    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."}
+        ]
+    }
+)