Core-S2L2A-249k

Core-S2L2A-249k is a curated subset of the Major-TOM Core-S2L2A dataset, containing 248,719 Sentinel-2 L2A image patches uniformly sampled across the globe. It serves as the source imagery for pre-computed embedding datasets used by the EarthEmbeddingExplorer cross-modal retrieval web application.

Overview

Property	Value
Source	Major-TOM Core-S2L2A
Sensor	Sentinel-2 MSI (Level-2A)
Number of patches	248,719
Patch size	384 × 384 pixels
Spectral bands	12 (B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12)
Spatial resolution	10 m / 20 m / 60 m (depending on band)
Output format	GeoParquet
License	CC-BY-SA-4.0

Sampling Strategy

This dataset was created by uniform grid sampling from the full Major-TOM Core-S2L2A archive:

1. A global grid is overlaid on the Major-TOM tile index.
2. For every 1/9 sampled grid cell, the central bounding box is selected as the crop region.
3. Each crop is extracted at a fixed size of 384 × 384 pixels to ensure consistency across all downstream embedding models.

This strategy guarantees spatial diversity while keeping the dataset size manageable for large-scale embedding generation and interactive web retrieval.

File Layout

.
├── metadata_249k.parquet          # Metadata and geospatial index (248,719 rows)
└── images_249k/
    ├── part_00001.parquet         # Image patches shard 1
    ├── part_00002.parquet         # Image patches shard 2
    └── ...

Metadata Schema (metadata_249k.parquet)

Column	Type	Description
product_id	string	Original Sentinel-2 product identifier
timestamp	datetime	Acquisition timestamp
grid_cell	string	Major-TOM grid cell identifier
grid_row_u	int16	Grid row index
grid_col_r	int16	Grid column index
geometry	geometry	WGS-84 polygon (footprint)
centre_lat	float32	Latitude of patch centre
centre_lon	float32	Longitude of patch centre
utm_footprint	string	Original UTM footprint as WKT
utm_crs	string	UTM CRS (e.g. EPSG:32633)
pixel_bbox	list	Pixel bounding box [x_min, y_min, x_max, y_max]
parquet_url	string	Path to the image shard containing this patch
parquet_row	int64	Row index within the image shard

Image Patch Schema (images_249k/part_*.parquet)

Each row contains a single 384 × 384 Sentinel-2 L2A patch stored as a 3-D array with shape (384, 384, 12) in uint16 format. The 12 bands follow the order:

[B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12]

Pre-computed Embedding Datasets

The following embedding datasets were computed from Core-S2L2A-249k using various foundation models. All embeddings share the same 248,719 samples and geospatial metadata, enabling fair cross-model comparison.

Filename	Embedding Model	Crop Size	Model Input Size	Embedding Dim	Source
SigLIP_crop_384x384.parquet	SigLIP (ViT-SO400M-14-SigLIP-384)	384×384	384×384	1152	Major-TOM/Core-S2RGB-249k-SigLIP
FarSLIP_crop_384x384.parquet	FarSLIP (ViT-B-16)	384×384	224×224	512	Major-TOM/Core-S2RGB-249k-FarSLIP
DINOv2_crop_384x384.parquet	DINOv2-large	384×384	224×224	1024	Major-TOM/Core-S2RGB-249k-DINOv2
SatCLIP_crop_384x384.parquet	SatCLIP (ViT16-L40)	384×384	224×224	256	Major-TOM/Core-S2L2A-249k-SatCLIP
Clay_crop_384x384.parquet	Clay v1.5	384×384	384×384	1024	Major-TOM/Core-S2L2A-249k-Clay-v1_5
OLMoEarth_Base_crop_384x384.parquet	OLMoEarth-Base	384×384	128×128	768	Major-TOM/Core-S2L2A-249k-OlmoEarth

Note: SigLIP, FarSLIP, and DINOv2 use RGB-only inputs (B04, B03, B02). SatCLIP, Clay, and OLMoEarth use multi-spectral inputs.

Usage

import pandas as pd

# Load metadata
meta = pd.read_parquet("metadata_249k.parquet")
print(len(meta), "patches")

# Load image patches from a shard
images = pd.read_parquet("images_249k/part_00001.parquet")
print(images.iloc[0]["B04"].shape)  # (384, 384)

Web Application

Explore these embeddings interactively with the EarthEmbeddingExplorer web application, supporting text, image, and geolocation queries.

Citation

If you use this dataset, please cite both the EarthEmbeddingExplorer tutorial paper and the original Major-TOM paper:

@article{zheng2026earthembeddingexplorer,
  title={EarthEmbeddingExplorer: A Web Application for Cross-Modal Retrieval of Global Satellite Images},
  author={Zheng, Yijie and Wu, Weijie and Wu, Bingyue and Zhao, Long and Li, Guoqing and Czerkawski, Mikolaj and Klemmer, Konstantin},
  journal={arXiv preprint arXiv:2603.29441},
  year={2026},
  note={ICLR 2026 Workshop ML4RS Tutorial Track (oral)}
}

@inproceedings{francis2024majortom,
  title={Major TOM: Expandable Datasets for Earth Observation},
  author={Francis, Alistair and Czerkawski, Mikolaj and others},
  year={2024},
  booktitle={IGARSS 2024},
  eprint={2402.12095},
  archivePrefix={arXiv}
}

License

This dataset is released under the CC-BY-SA-4.0 license.