English

Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models

Computer Vision and Pattern Recognition 2025-06-11 v1 Machine Learning

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.

Keywords

Cite

@article{arxiv.2506.08780,
  title  = {Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models},
  author = {Isaac Corley and Lakshay Sharma and Ruth Crasto},
  journal= {arXiv preprint arXiv:2506.08780},
  year   = {2025}
}
R2 v1 2026-07-01T03:09:04.523Z