SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
Adam Stewart, Nils Lehmann, Isaac Corley, Yi Wang, Yi-Chia Chang, Nassim Ait, Shradha Sehgal, Caleb Robinson, Arindam Banerjee. "SSL4EO-L: Datasets and Foundation Models for Landsat Imagery." Advances in Neural Information Processing Systems (NeurIPS), 2024.
We introduce SSL4EO-L, the first ever dataset designed for self-supervised learning for Earth Observation for the Landsat family of satellites.
Figure 1.Geographical distribution of the SSL4EO-L dataset, including the (a) Landsat 8–9 OLI/TIRS, (b) Landsat 4–5 TM, and (c) Landsat 7 ETM+ splits. Surface reflectance (SR) and top of atmosphere (TOA) products are sampled from the same locations per sensor.
Cite as:
@article{stewart2024ssl4eo,
author = "Stewart, Adam and Lehmann, Nils and Corley, Isaac and Wang, Yi and Chang, Yi-Chia and Ait Ali Braham, Nassim Ait and Sehgal, Shradha and Robinson, Caleb and Banerjee, Arindam",
title = "SSL4EO-L: Datasets and Foundation Models for Landsat Imagery",
journal = "Advances in Neural Information Processing Systems (NeurIPS)",
volume = "36",
year = "2024",
url = "https://proceedings.neurips.cc/paper_files/paper/2023/hash/bbf7ee04e2aefec136ecf60e346c2e61-Abstract-Datasets_and_Benchmarks.html"
}