license: cc-by-4.0
pretty_name: SSL4EO-S12-downstream
task_categories:
- other
language: en
tags:
- earth-observation
- satellite-imagery
- sentinel
configs:
- config_name: data_dev
data_files: data_dev/*
SSL4EO-S12-downstream
Welcome to the SSL4EO-S12-downstream dataset. This dataset is used in the Embed2Scale Challenge.
The Test phase challenge data is available
The test phase challenge data is now available under the data_eval folder. It comprises 8111 datacubes, ~90 GB, of the same format as the dev set.
The data constitutes two sets, the dev set of 5149 datacubes and the test set of 8111 datacubes, approximately 60 GB and 90 GB, respectively. The datacubes are visualized below and contain Sentinel-1 and Sentinel-2 data. The data is organized under the data_dev and data_eval folders, which contains one subfolder per modality (s1, s2l1c and s2l2a) where the datacubes reside. Each datacube constitute one location, with S1 VV and VH polarisations, S2 L1C and S2 L2A channels. Each location is sampled at four times, one during months March-May, one during June-August, one during September-November and finally one during months December-February, in this order. The datacubes are stored in zipped zarr files; see here for instructions how to load the data. The data in the zarr files is structured as (number of locations, number of timestamps, number of channels, heigh, width) with the dimensions (1, 4, 27, 264, 264); the 27 channels coming from 2 S1 polarizations (VV and VH), 13 S2 L1C channels (B1, B2, B3, B4, B5, B6, B7, B8, B8A, B9, B10, B11, B12), and 12 S2 L2A channels (B1, B2, B3, B4, B5, B6, B7, B8, B8A, B9, B11, B12).
The data is structured identically to the SSL4EOS12 v1.1 dataset:
@article{blumenstiel2025ssl4eos12,
title={{SSL4EOS12 v1.1 - A Multimodal, Multiseasonal Dataset for Pretraining}},
author={Blumenstiel, Benedikt and Braham, Nassim Ait Ali and Albrecht, Conrad M and Maurogiovanni, Stefano and Fraccaro, Paolo},
journal={arXiv preprint arXiv:2503.00168},
year={2025}
}
which is based on
@article{wang2022ssl4eo,
title={{SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation}},
author={Wang, Yi and Braham, Nassim Ait Ali and Xiong, Zhitong and Liu, Chenying and Albrecht, Conrad M and Zhu, Xiao Xiang},
journal={arXiv preprint arXiv:2211.07044},
year={2022}
}