mlsanityData to 14 Oct 2026

Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models

arXiv 2506.08780 ↗First posted 10 Jun 2025cs.CV cs.LGcited by 3

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 33 references that are in the map. First posted on arXiv 10 Jun 2025.

Builds on

15 of 33 references.

References · 15

  1. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  2. 2020Improved Baselines with Momentum Contrastive Learningcited by 2,287
  3. 2017EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classificationcited by 1,496
  4. 2022SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagerycited by 408
  5. 2017Functional Map of the Worldcited by 338
  6. 2019BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understandingcited by 234
  7. 2023GEO-Bench: Toward Foundation Models for Earth Monitoringcited by 124
  8. 2023On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligencecited by 88
  9. 2025Towards a Unified Copernicus Foundation Model for Earth Visioncited by 53
  10. 2023SSL4EO-L: Datasets and Foundation Models for Landsat Imagerycited by 49
  11. 2023Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensingcited by 48
  12. 2019In-domain representation learning for remote sensingcited by 41
3 more
  1. 2024Multi-Label Guided Soft Contrastive Learning for Efficient Earth Observation Pretrainingcited by 28
  2. 2023Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matterscited by 27
  3. 2021Active Fire Detection in Landsat-8 Imagery: a Large-Scale Dataset and a Deep-Learning Studycited by 21

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026How do Self-Supervised Remote Sensing Vision Models Transfer to Downstream Tasks?cited by 0
  2. 2026HeatCast: A Benchmark for Neighborhood-Scale LST Forecasting across 124 U.S. Citiescited by 0
  3. 2026Earth Observation Foundation Models for Terrestrial Ecohydrology: From Representation Learning to Process Inferencecited by 0