mlsanityData to 14 Oct 2026

GEO-Bench: Toward Foundation Models for Earth Monitoring

arXiv 2306.03831 ↗First posted 6 Jun 2023cs.LG cs.CVcited by 124

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Abstract (arXiv)

Recent progress in self-supervision has shown that pre-training large neural networks on vast amounts of unsupervised data can lead to substantial increases in generalization to downstream tasks. Such models, recently coined foundation models, have been transformational to the field of natural language processing. Variants have also been proposed for image data, but their applicability to remote sensing tasks is limited. To stimulate the development of foundation models for Earth monitoring, we propose a benchmark comprised of six classification and six segmentation tasks, which were carefully curated and adapted to be both relevant to the field and well-suited for model evaluation. We accompany this benchmark with a robust methodology for evaluating models and reporting aggregated results to enable a reliable assessment of progress. Finally, we report results for 20 baselines to gain information about the performance of existing models. We believe that this benchmark will be a driver of progress across a variety of Earth monitoring tasks.

Key facts. Cited by 124 papers in the map (data through 14 Oct 2026). Builds on 45 of its 87 references that are in the map. First posted on arXiv 6 Jun 2023.

Builds on

45 of 87 references.

References · 45

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 27; 2025: 43; 2026: 51.

124 papers.

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  1. 2023SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagerycited by 151
  2. 2024Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applicationscited by 144
  3. 2024Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observationcited by 104
  4. 2024Mission Critical -- Satellite Data is a Distinct Modality in Machine Learningcited by 77
  5. 2024MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learningcited by 77
  6. 2024AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalitiescited by 74
  7. 2025Towards a Unified Copernicus Foundation Model for Earth Visioncited by 53
  8. 2025Galileo: Learning Global & Local Features of Many Remote Sensing Modalitiescited by 43
  9. 2024One for All: Toward Unified Foundation Models for Earth Visioncited by 34
  10. 2025Panopticon: Advancing Any-Sensor Foundation Models for Earth Observationcited by 34
  11. 2024On the Foundations of Earth and Climate Foundation Modelscited by 33
  12. 2023FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoringcited by 31
38 more
  1. 2024TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learningcited by 31
  2. 2024Large Language Models for Captioning and Retrieving Remote Sensing Imagescited by 30
  3. 2024Multi-Label Guided Soft Contrastive Learning for Efficient Earth Observation Pretrainingcited by 28
  4. 2024PhilEO Bench: Evaluating Geo-Spatial Foundation Modelscited by 25
  5. 2025TerraTorch: The Geospatial Foundation Models Toolkitcited by 25
  6. 2024Specialized Foundation Models Struggle to Beat Supervised Baselinescited by 24
  7. 2025OlmoEarth: Stable Latent Image Modeling for Multimodal Earth Observationcited by 24
  8. 2025Multi-Agent Geospatial Copilots for Remote Sensing Workflowscited by 22
  9. 2025GEO-Bench-2: From Performance to Capability, Rethinking Evaluation in Geospatial AIcited by 21
  10. 2025GeoChain: Multimodal Chain-of-Thought for Geographic Reasoningcited by 16
  11. 2023OpenForest: A data catalogue for machine learning in forest monitoringcited by 15
  12. 2024Mind the Modality Gap: Towards a Remote Sensing Vision-Language Model via Cross-modal Alignmentcited by 15
  13. 2025SciHorizon: Benchmarking AI-for-Science Readiness from Scientific Data to Large Language Modelscited by 15
  14. 2024Knowledge-guided Machine Learning: Current Trends and Future Prospectscited by 14
  15. 2024OAM-TCD: A globally diverse dataset of high-resolution tree cover mapscited by 14
  16. 2024A Change Detection Reality Checkcited by 13
  17. 2024WildSAT: Learning Satellite Image Representations from Wildlife Observationscited by 13
  18. 2025From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Modelscited by 12
  19. 2026No One Knows the State of the Art in Geospatial Foundation Modelscited by 12
  20. 2024Contrastive ground-level image and remote sensing pre-training improves representation learning for natural world imagerycited by 10
  21. 2025Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?cited by 10
  22. 2025Geospatial Foundation Models to Enable Progress on Sustainable Development Goalscited by 10
  23. 2025Fine-tune Smarter, Not Harder: Parameter-Efficient Fine-Tuning for Geospatial Foundation Modelscited by 9
  24. 2024Evaluating and Benchmarking Foundation Models for Earth Observation and Geospatial AIcited by 8
  25. 2025DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observationcited by 7
  26. 2026MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Trainingcited by 7
  27. 2024Multi-Spectral Remote Sensing Image Retrieval Using Geospatial Foundation Modelscited by 6
  28. 2024M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Datacited by 6
  29. 2025Deploying Geospatial Foundation Models in the Real World: Lessons from WorldCerealcited by 6
  30. 2024How Effective is Pre-training of Large Masked Autoencoders for Downstream Earth Observation Tasks?cited by 5
  31. 2025Ice-FMBench: A Foundation Model Benchmark for Sea Ice Type Segmentationcited by 5
  32. 2025SSL4Eco: A Global Seasonal Dataset for Geospatial Foundation Models in Ecologycited by 5
  33. 2025ExEBench: Benchmarking Foundation Models on Extreme Earth Eventscited by 5
  34. 2025MultiMAE Meets Earth Observation: Pre-training Multi-modal Multi-task Masked Autoencoders for Earth Observation Taskscited by 5
  35. 2025SpectralX: Parameter-efficient Domain Generalization for Spectral Remote Sensing Foundation Modelscited by 5
  36. 2026CITYREP: A Unified Benchmark for Urban Representations Across Cities, Tasks, and Modalitiescited by 5
  37. 2026UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observationcited by 5
  38. 2025Foundation Models for Environmental Science: A Survey of Emerging Frontierscited by 4

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