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Major-TOM/Core-S2L2A

Core-S2L2A Contains a global coverage of Sentinel-2 (Level 2A) patches, each of size 1,068 x 1,068 pixels. Source Sensing Type Number of Patches Patch Size Total Pixels Sentinel-2 Level-2A Optical Multispectral 2,245,886 1,068 x 1,068 (10 m) > 2.564 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)… See the full description on the dataset page: https://huggingface.co/datasets/Major-TOM/Core-S2L2A.

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Dataset Card

Core-S2L2A

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

SourceSensing TypeNumber of PatchesPatch SizeTotal Pixels
Sentinel-2 Level-2AOptical Multispectral2,245,8861,068 x 1,068 (10 m)> 2.564 Trillion

Content

ColumnDetailsResolution
B01Coastal aerosol, 442.7 nm (S2A), 442.3 nm (S2B)60m
B02Blue, 492.4 nm (S2A), 492.1 nm (S2B)10m
B03Green, 559.8 nm (S2A), 559.0 nm (S2B)10m
B04Red, 664.6 nm (S2A), 665.0 nm (S2B)10m
B05Vegetation red edge, 704.1 nm (S2A), 703.8 nm (S2B)20m
B06Vegetation red edge, 740.5 nm (S2A), 739.1 nm (S2B)20m
B07Vegetation red edge, 782.8 nm (S2A), 779.7 nm (S2B)20m
B08NIR, 832.8 nm (S2A), 833.0 nm (S2B)10m
B8ANarrow NIR, 864.7 nm (S2A), 864.0 nm (S2B)20m
B09Water vapour, 945.1 nm (S2A), 943.2 nm (S2B)60m
B11SWIR, 1613.7 nm (S2A), 1610.4 nm (S2B)20m
B12SWIR, 2202.4 nm (S2A), 2185.7 nm (S2B)20m
cloud_maskCloud Mask produced by SEnSeI10m
thumbnailRGB composite [B04, B03, B02] saved as png10m

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:

python
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-S2L2A/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](https://arxiv.org/abs/2402.12095/)

latex
@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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