mlsanityData to 7 Oct 2026

In-domain representation learning for remote sensing

arXiv 1911.06721 ↗First posted 15 Nov 2019cs.CVcited by 41

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Abstract (arXiv)

Given the importance of remote sensing, surprisingly little attention has been paid to it by the representation learning community. To address it and to establish baselines and a common evaluation protocol in this domain, we provide simplified access to 5 diverse remote sensing datasets in a standardized form. Specifically, we investigate in-domain representation learning to develop generic remote sensing representations and explore which characteristics are important for a dataset to be a good source for remote sensing representation learning. The established baselines achieve state-of-the-art performance on these datasets.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Nov 2019.

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Citing papers per year: 2021: 6; 2022: 5; 2023: 7; 2024: 12; 2025: 9; 2026: 2.

41 papers.

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  1. 2022SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagerycited by 402
  2. 2022Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learningcited by 302
  3. 2023SpectralGPT: Spectral Remote Sensing Foundation Modelcited by 250
  4. 2021Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Datacited by 214
  5. 2023Towards Geospatial Foundation Models via Continual Pretrainingcited by 109
  6. 2023Lightweight, Pre-trained Transformers for Remote Sensing Timeseriescited by 102
  7. 2024Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagerycited by 82
  8. 2021Self-Supervised Pretraining Improves Self-Supervised Pretrainingcited by 81
  9. 2021TorchGeo: Deep Learning With Geospatial Datacited by 73
  10. 2024MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretrainingcited by 66
  11. 2025Towards a Unified Copernicus Foundation Model for Earth Visioncited by 52
  12. 2021Self-Supervised Material and Texture Representation Learning for Remote Sensing Taskscited by 49
29 more
  1. 2024Bridging Remote Sensors with Multisensor Geospatial Foundation Modelscited by 46
  2. 2023Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matterscited by 27
  3. 2024Multi-Label Guided Soft Contrastive Learning for Efficient Earth Observation Pretrainingcited by 27
  4. 2023Extending global-local view alignment for self-supervised learning with remote sensing imagerycited by 20
  5. 2023Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysiscited by 14
  6. 2024SwiMDiff: Scene-wide Matching Contrastive Learning with Diffusion Constraint for Remote Sensing Imagecited by 14
  7. 2024WildSAT: Learning Satellite Image Representations from Wildlife Observationscited by 13
  8. 2024SeaMo: A Season-Aware Multimodal Foundation Model for Remote Sensingcited by 10
  9. 2021Damage detection using in-domain and cross-domain transfer learningcited by 7
  10. 2021Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mappingcited by 6
  11. 2023Self-Supervised In-Domain Representation Learning for Remote Sensing Image Scene Classificationcited by 4
  12. 2026From Pixels to Patches: Pooling Strategies for Earth Embeddingscited by 4
  13. 2022Evaluating the Label Efficiency of Contrastive Self-Supervised Learning for Multi-Resolution Satellite Imagerycited by 3
  14. 2025Towards Efficient Benchmarking of Foundation Models in Remote Sensing: A Capabilities Encoding Approachcited by 3
  15. 2025Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Modelscited by 3
  16. 2022Self-Supervised Pretraining on Satellite Imagery: a Case Study on Label-Efficient Vehicle Detectioncited by 2
  17. 2024WV-Net: A foundation model for SAR WV-mode satellite imagery trained using contrastive self-supervised learning on 10 million imagescited by 2
  18. 2024ViGEO: an Assessment of Vision GNNs in Earth Observationcited by 1
  19. 2024A Label Propagation Strategy for CutMix in Multi-Label Remote Sensing Image Classificationcited by 1
  20. 2025Improving Remote Sensing Classification using Topological Data Analysis and Convolutional Neural Networkscited by 1
  21. 2025Neighborhood Feature Pooling for Remote Sensing Image Classificationcited by 1
  22. 2022Learning latent representations for operational nitrogen response rate predictioncited by 0
  23. 2024Remote Diffusioncited by 0
  24. 2024Edge-Cloud Collaborative Satellite Image Analysis for Efficient Man-Made Structure Recognitioncited by 0
  25. 2025i-WiViG: Interpretable Window Vision GNNcited by 0
  26. 2025RSRWKV: A Linear-Complexity 2D Attention Mechanism for Efficient Remote Sensing Vision Taskcited by 0
  27. 2025GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language Modelscited by 0
  28. 2025Do Satellite Tasks Need Special Pretraining?cited by 0
  29. 2026Prototype-based Explainable Neural Networks with Channel-specific Reasoning for Geospatial Learning Taskscited by 0