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Core-S2L1C

Contains a global coverage of Sentinel-2 (Level 1C) patches, each of size 1,068 x 1,068 pixels.

Source Sensing Type Number of Patches Patch Size Total Pixels
Sentinel-2 Level-1C Optical Multispectral 2,245,886 1,068x1,068 2.56 Trillion

Content

Column Details Resolution
B01 Coastal aerosol, 442.7 nm (S2A), 442.3 nm (S2B) 60m
B02 Blue, 492.4 nm (S2A), 492.1 nm (S2B) 10m
B03 Green, 559.8 nm (S2A), 559.0 nm (S2B) 10m
B04 Red, 664.6 nm (S2A), 665.0 nm (S2B) 10m
B05 Vegetation red edge, 704.1 nm (S2A), 703.8 nm (S2B) 20m
B06 Vegetation red edge, 740.5 nm (S2A), 739.1 nm (S2B) 20m
B07 Vegetation red edge, 782.8 nm (S2A), 779.7 nm (S2B) 20m
B08 NIR, 832.8 nm (S2A), 833.0 nm (S2B) 10m
B8A Narrow NIR, 864.7 nm (S2A), 864.0 nm (S2B) 20m
B09 Water vapour, 945.1 nm (S2A), 943.2 nm (S2B) 60m
B10 SWIR – Cirrus, 1373.5 nm (S2A), 1376.9 nm (S2B) 60m
B11 SWIR, 1613.7 nm (S2A), 1610.4 nm (S2B) 20m
B12 SWIR, 2202.4 nm (S2A), 2185.7 nm (S2B) 20m
cloud_mask Cloud Mask produced by SEnSeI 10m
thumbnail RGB composite [B04, B03, B02] saved as png 10m

Spatial Coverage

This is a global monotemporal dataset. Nearly every piece of Earth captured by Sentinel-2 is contained at least once in this dataset (and only once, excluding some marginal overlaps).

The following figure demonstrates the spatial coverage (only black pixels are absent): image/png

Example Use

Interface scripts are available at https://github.com/ESA-PhiLab/Major-TOM

Here's a sneak peek with a thumbnail image:

from fsspec.parquet import open_parquet_file
import pyarrow.parquet as pq
from io import BytesIO
from PIL import Image

PARQUET_FILE = 'part_03900' # parquet number
ROW_INDEX = 42 # row number (about 500 per parquet)

url = "https://huggingface.co./datasets/Major-TOM/Core-S2L1C/resolve/main/images/{}.parquet".format(PARQUET_FILE)
with open_parquet_file(url,columns = ["thumbnail"]) as f:
    with pq.ParquetFile(f) as pf:
        first_row_group = pf.read_row_group(ROW_INDEX, columns=['thumbnail'])

stream = BytesIO(first_row_group['thumbnail'][0].as_py())
image = Image.open(stream)

Cite

arxiv

@inproceedings{Major_TOM,
  title={Major TOM: Expandable Datasets for Earth Observation}, 
  author={Alistair Francis and Mikolaj Czerkawski},
  year={2024},
  booktitle={IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium}, 
  eprint={2402.12095},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

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