Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models

Isaac Corley, Lakshay Sharma, Ruth Crasto
6/10/2025
cs.CVcs.LG

No official code found. Best implementation: isaaccorley/landsatbench (20 stars, MIT, PyTorch, last commit 2025-06-18).

Abstract

The Landsat program offers over 50 years of globally consistent Earth imagery. However, the lack of benchmarks for this data constrains progress towards Landsat-based Geospatial Foundation Models (GFM). In this paper, we introduce Landsat-Bench, a suite of three benchmarks with Landsat imagery that adapt from existing remote sensing datasets -- EuroSAT-L, BigEarthNet-L, and LC100-L. We establish baseline and standardized evaluation methods across both common architectures and Landsat foundation models pretrained on the SSL4EO-L dataset. Notably, we provide evidence that SSL4EO-L pretrained GFMs extract better representations for downstream tasks in comparison to ImageNet, including performance gains of +4% OA and +5.1% mAP on EuroSAT-L and BigEarthNet-L.

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Code Implementations(1)

isaaccorley/landsatbenchCommunity100%
PyTorchMIT

Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models

201Python, Jupyter NotebookJun 11, 20251 years agoMIT
benchmarksgeospatiallandsatpytorch

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Cite this paper

@article{corley2025landsatbench,
  title  = {Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models},
  author = {Isaac Corley and Lakshay Sharma and Ruth Crasto},
  year   = {2025},
  eprint = {2506.08780},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.08780v1}
}

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