SEN12MS – A CURATED DATASET OF GEOREFERENCED MULTI-SPECTRAL SENTINEL-1/2 IMAGERY FOR DEEP LEARNING AND DATA FUSION

147 citations as recorded by crossref.

1. TimeSen2Crop: A Million Labeled Samples Dataset of Sentinel 2 Image Time Series for Crop-Type Classification G. Weikmann et al. 10.1109/JSTARS.2021.3073965
2. SwiMDiff: Scene-Wide Matching Contrastive Learning With Diffusion Constraint for Remote Sensing Image J. Tian et al. 10.1109/TGRS.2024.3371481
3. Multi-Scale Feature Fusion Network with Symmetric Attention for Land Cover Classification Using SAR and Optical Images D. Xu et al. 10.3390/rs16060957
4. Report on the 2020 IEEE GRSS Data Fusion Contest-Global Land Cover Mapping With Weak Supervision [Technical Committees] N. Yokoya et al. 10.1109/MGRS.2020.3033515
5. Forensic research of satellite images forgery: a comprehensive survey X. Ding et al. 10.1007/s10462-024-10909-w
6. Forest Disturbance Detection via Self-Supervised and Transfer Learning With Sentinel-1&2 Images R. Kuzu et al. 10.1109/JSTARS.2024.3361183
7. Clean Collector Algorithm for Satellite Image Pre-Processing of SAR-to-EO Translation M. Kim et al. 10.3390/electronics13224529
8. LM-Net: A Lightweight Matching Network for Remote Sensing Image Matching and Registration D. Quan et al. 10.1109/TGRS.2024.3509638
9. SSL4EO-S12: A large-scale multimodal, multitemporal dataset for self-supervised learning in Earth observation [Software and Data Sets] Y. Wang et al. 10.1109/MGRS.2023.3281651
10. High-Resolution Land Cover Mapping Through Learning With Noise Correction R. Dong et al. 10.1109/TGRS.2021.3068280
11. Self-Supervised Learning for Invariant Representations From Multi-Spectral and SAR Images P. Jain et al. 10.1109/JSTARS.2022.3204888
12. Multilevel Feature Fusion-Based CNN for Local Climate Zone Classification From Sentinel-2 Images: Benchmark Results on the So2Sat LCZ42 Dataset C. Qiu et al. 10.1109/JSTARS.2020.2995711
13. A global multimodal flood event dataset with heterogeneous text and multi-source remote sensing images Z. Zhang et al. 10.1080/20964471.2024.2358615
14. There Are No Data Like More Data: Datasets for deep learning in Earth observation M. Schmitt et al. 10.1109/MGRS.2023.3293459
15. Towards global flood mapping onboard low cost satellites with machine learning G. Mateo-Garcia et al. 10.1038/s41598-021-86650-z
16. Removing Cloud Cover Interference from Sentinel-2 imagery in Google Earth Engine by fusing Sentinel-1 SAR data with a CNN model X. Zhang et al. 10.1080/01431161.2021.2012295
17. Graph-Based Propagation for Multispectral Remote Sensing Image Completion I. Rolland et al. 10.1109/TGRS.2025.3527056
18. Review of pixel-level remote sensing image fusion based on deep learning Z. Wang et al. 10.1016/j.inffus.2022.09.008
19. Benchmarking and scaling of deep learning models for land cover image classification I. Papoutsis et al. 10.1016/j.isprsjprs.2022.11.012
20. Multisensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery P. Ebel et al. 10.1109/TGRS.2020.3024744
21. A Deep Learning Approach to an Enhanced Building Footprint and Road Detection in High-Resolution Satellite Imagery C. Ayala et al. 10.3390/rs13163135
22. Distilled Heterogeneous Feature Alignment Network for SAR Image Semantic Segmentation M. Gao et al. 10.1109/LGRS.2023.3293160
23. Deep-Learning-Based Semantic Segmentation of Remote Sensing Images: A Survey L. Huang et al. 10.1109/JSTARS.2023.3335891
24. Learning-Based Near-Infrared Band Simulation with Applications on Large-Scale Landcover Classification X. Yuan et al. 10.3390/s23094179
25. TorchGeo: Deep Learning With Geospatial Data A. Stewart et al. 10.1145/3707459
26. GFTT: Geographical Feature Tokenization Transformer for SAR-to-Optical Image Translation H. Liang et al. 10.1109/JSTARS.2024.3523274
27. FG-GAN: A Fine-Grained Generative Adversarial Network for Unsupervised SAR-to-Optical Image Translation X. Yang et al. 10.1109/TGRS.2022.3165371
28. Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion A. Meraner et al. 10.1016/j.isprsjprs.2020.05.013
29. Multi-Relation Attention Network for Image Patch Matching D. Quan et al. 10.1109/TIP.2021.3101414
30. TransFusion-CR: Two-Phase SAR-to-Optical Translation and Deep Feature Fusion for Cloud Removal R. Liu et al. 10.1109/TGRS.2024.3439854
31. Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience: A Survey M. Savelonas et al. 10.3390/rs14236017
32. S1S2-Water: A Global Dataset for Semantic Segmentation of Water Bodies From Sentinel- 1 and Sentinel-2 Satellite Images M. Wieland et al. 10.1109/JSTARS.2023.3333969
33. A Weakly Supervised Semantic Segmentation Framework for Medium-Resolution Forest Classification With Noisy Labels and GF-1 WFV Images X. Peng et al. 10.1109/TGRS.2024.3404953
34. A super-ensemble approach to map land cover types with high resolution over data-sparse African savanna landscapes L. Song et al. 10.1016/j.jag.2022.103152
35. Semi-Supervised Learning for Joint SAR and Multispectral Land Cover Classification A. Montanaro et al. 10.1109/LGRS.2022.3195259
36. Land Use and Land Cover Classification Meets Deep Learning: A Review S. Zhao et al. 10.3390/s23218966
37. MLRSNet: A multi-label high spatial resolution remote sensing dataset for semantic scene understanding X. Qi et al. 10.1016/j.isprsjprs.2020.09.020
38. Explaining the Effects of Clouds on Remote Sensing Scene Classification J. Gawlikowski et al. 10.1109/JSTARS.2022.3221788
39. 3DMAE: Joint SAR and Optical Representation Learning With Vertical Masking L. Zhang et al. 10.1109/LGRS.2023.3316193
40. Self-Distillation Feature Learning Network for Optical and SAR Image Registration D. Quan et al. 10.1109/TGRS.2022.3173476
41. Google Earth Engine: A Global Analysis and Future Trends A. Velastegui-Montoya et al. 10.3390/rs15143675
42. Interband Retrieval and Classification Using the Multilabeled Sentinel-2 BigEarthNet Archive U. Chaudhuri et al. 10.1109/JSTARS.2021.3112209
43. Ship Detection in Sentinel 2 Multi-Spectral Images with Self-Supervised Learning A. Ciocarlan & A. Stoian 10.3390/rs13214255
44. A Review of Optical and SAR Image Deep Feature Fusion in Semantic Segmentation C. Liu et al. 10.1109/JSTARS.2024.3424831
45. Reconstruction Bias U-Net for Road Extraction From Optical Remote Sensing Images Z. Chen et al. 10.1109/JSTARS.2021.3053603
46. SEN12MS-CR-TS: A Remote-Sensing Data Set for Multimodal Multitemporal Cloud Removal P. Ebel et al. 10.1109/TGRS.2022.3146246
47. Deep Species Distribution Modeling From Sentinel-2 Image Time-Series: A Global Scale Analysis on the Orchid Family J. Estopinan et al. 10.3389/fpls.2022.839327
48. Learning SAR-to-Optical Image Translation via Diffusion Models With Color Memory Z. Guo et al. 10.1109/JSTARS.2024.3439516
49. Beyond Supervised Learning in Remote Sensing: A Systematic Review of Deep Learning Approaches B. Hosseiny et al. 10.1109/JSTARS.2023.3316733
50. Learning a Joint Embedding of Multiple Satellite Sensors: A Case Study for Lake Ice Monitoring M. Tom et al. 10.1109/TGRS.2022.3211184
51. When Remote Sensing Meets Foundation Model: A Survey and Beyond C. Huo et al. 10.3390/rs17020179
52. Global Land-Cover Mapping With Weak Supervision: Outcome of the 2020 IEEE GRSS Data Fusion Contest C. Robinson et al. 10.1109/JSTARS.2021.3063849
53. Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities L. Zhang & L. Zhang 10.1109/MGRS.2022.3145854
54. U-Net feature fusion for multi-class semantic segmentation of urban fabrics from Sentinel-2 imagery: an application on Grand Est Region, France R. Wenger et al. 10.1080/01431161.2022.2054295
55. Cross-resolution national-scale land-cover mapping based on noisy label learning: A case study of China Y. Liu et al. 10.1016/j.jag.2023.103265
56. Multimodal Supervised Contrastive Learning in Remote Sensing Downstream Tasks P. Berg et al. 10.1109/LGRS.2024.3385995
57. 2020 IEEE GRSS Data Fusion Contest: Global Land Cover Mapping With Weak Supervision [Technical Committees] N. Yokoya et al. 10.1109/MGRS.2020.2970124
58. OpenForest: a data catalog for machine learning in forest monitoring A. Ouaknine et al. 10.1017/eds.2024.53
59. A Globally Applicable Method for NDVI Estimation from Sentinel-1 SAR Backscatter Using a Deep Neural Network and the SEN12TP Dataset T. Roßberg & M. Schmitt 10.1007/s41064-023-00238-y
60. On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances, and Million-AID Y. Long et al. 10.1109/JSTARS.2021.3070368
61. CERMF-Net: A SAR-Optical Feature Fusion for Cloud Elimination From Sentinel-2 Imagery Using Residual Multiscale Dilated Network J. Anandakrishnan et al. 10.1109/JSTARS.2024.3411032
62. Review on Convolutional Neural Networks (CNN) in vegetation remote sensing T. Kattenborn et al. 10.1016/j.isprsjprs.2020.12.010
63. deepNIR: Datasets for Generating Synthetic NIR Images and Improved Fruit Detection System Using Deep Learning Techniques I. Sa et al. 10.3390/s22134721
64. AmazonCRIME: un conjunto de datos y punto de referencia de Inteligencia Artificial Geoespacial para la clasificación de áreas potenciales vinculadas a Crímenes Ambientales Transnacionales en la Selva Amazónica J. Pinto-Hidalgo & J. Silva-Centeno 10.4995/raet.2022.15710
65. Advancing horizons in remote sensing: a comprehensive survey of deep learning models and applications in image classification and beyond S. Paheding et al. 10.1007/s00521-024-10165-7
66. AIR-POLSAR-CR1.0: A Benchmark Dataset for Cloud Removal in High-Resolution Optical Remote Sensing Images with Fully Polarized SAR Y. Wang et al. 10.3390/rs17020275
67. Contrastive Self-Supervised Learning for Globally Distributed Landslide Detection O. Ghorbanzadeh et al. 10.1109/ACCESS.2024.3449447
68. The Eyes of the Gods: A Survey of Unsupervised Domain Adaptation Methods Based on Remote Sensing Data M. Xu et al. 10.3390/rs14174380
69. Deep Image Prior Amplitude SAR Image Anonymization E. Cannas et al. 10.3390/rs15153750
70. NaSC-TG2: Natural Scene Classification With Tiangong-2 Remotely Sensed Imagery Z. Zhou et al. 10.1109/JSTARS.2021.3063096
71. Towards Synoptic Water Monitoring Systems: A Review of AI Methods for Automating Water Body Detection and Water Quality Monitoring Using Remote Sensing L. Yang et al. 10.3390/s22062416
72. Bare Soil Extraction from Sentinel-2 Images with Weakly Supervised and Spectral Index 燚. 赵 10.12677/JSTA.2024.121005
73. High-Resolution Land-Cover Mapping Based on a Cross-Resolution Deep Learning Framework and Available Low-Resolution Labels X. Qi et al. 10.1109/JSTARS.2023.3342994
74. A Workflow for Collecting and Preprocessing Sentinel-1 Images for Time Series Prediction Suitable for Deep Learning Algorithms W. Moskolaï et al. 10.3390/geomatics2040024
75. Large-Scale Land Cover Mapping Framework Based on Prior Product Label Generation: A Case Study of Cambodia H. Zhu et al. 10.3390/rs16132443
76. Meta-FSEO: A Meta-Learning Fast Adaptation with Self-Supervised Embedding Optimization for Few-Shot Remote Sensing Scene Classification Y. Li et al. 10.3390/rs13142776
77. Two-Way Generation of High-Resolution EO and SAR Images via Dual Distortion-Adaptive GANs Y. Qing et al. 10.3390/rs15071878
78. A framework for large-scale mapping of human settlement extent from Sentinel-2 images via fully convolutional neural networks C. Qiu et al. 10.1016/j.isprsjprs.2020.01.028
79. Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review—Part II: Applications T. Hoeser et al. 10.3390/rs12183053
80. WTS: A Weakly towards Strongly Supervised Learning Framework for Remote Sensing Land Cover Classification Using Segmentation Models W. Zhang et al. 10.3390/rs13030394
81. Feature Interaction Learning Network for Cross-Spectral Image Patch Matching C. Yu et al. 10.1109/TIP.2023.3313488
82. Combining Deep Learning and Multi-Source GIS Methods to Analyze Urban and Greening Changes M. Francini et al. 10.3390/s23083805
83. Cloud-Guided Fusion With SAR-to-Optical Translation for Thick Cloud Removal X. Xiang et al. 10.1109/TGRS.2024.3431556
84. GLUENet: An Efficient Network for Remote Sensing Image Dehazing with Gated Linear Units and Efficient Channel Attention J. Fang et al. 10.3390/rs16081450
85. MapInWild: A remote sensing dataset to address the question of what makes nature wild [Software and Data Sets] B. Ekim et al. 10.1109/MGRS.2022.3226525
86. Water body classification from high-resolution optical remote sensing imagery: Achievements and perspectives Y. Li et al. 10.1016/j.isprsjprs.2022.03.013
87. Flood Detection with SAR: A Review of Techniques and Datasets D. Amitrano et al. 10.3390/rs16040656
88. DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin E. Cherif et al. 10.3390/rs14195000
89. TreeSatAI Benchmark Archive: a multi-sensor, multi-label dataset for tree species classification in remote sensing S. Ahlswede et al. 10.5194/essd-15-681-2023
90. Joint Network Combining Dual-Attention Fusion Modality and Two Specific Modalities for Land Cover Classification Using Optical and SAR Images X. Liu et al. 10.1109/JSTARS.2023.3347571
91. ISSLIDE: A New InSAR Dataset for Slow SLIding Area DEtection With Machine Learning A. Bralet et al. 10.1109/LGRS.2024.3365299
92. A Novel Coarse-to-Fine Deep Learning Registration Framework for Multimodal Remote Sensing Images D. Quan et al. 10.1109/TGRS.2023.3306042
93. cuFSDAF: An Enhanced Flexible Spatiotemporal Data Fusion Algorithm Parallelized Using Graphics Processing Units H. Gao et al. 10.1109/TGRS.2021.3080384
94. Rearranging Pixels is a Powerful Black-Box Attack for RGB and Infrared Deep Learning Models J. Pomponi et al. 10.1109/ACCESS.2023.3241360
95. Cloud removal for optical remote sensing imagery using the SPA-CycleGAN network R. Jing et al. 10.1117/1.JRS.16.034520
96. A Unified Deep Learning Network for Remote Sensing Image Registration and Change Detection R. Zhou et al. 10.1109/TGRS.2023.3344751
97. Cloud Removal Based on SAR-Optical Remote Sensing Data Fusion via a Two-Flow Network R. Mao et al. 10.1109/JSTARS.2022.3203508
98. AgriSen-COG, a Multicountry, Multitemporal Large-Scale Sentinel-2 Benchmark Dataset for Crop Mapping Using Deep Learning T. Selea 10.3390/rs15122980
99. Exploring Archetypes of Tropical Fire-Related Forest Disturbances Based on Dense Optical and Radar Satellite Data and Active Fire Alerts J. Balling et al. 10.3390/f12040456
100. Hash-Based Remote Sensing Image Retrieval L. Han et al. 10.1109/TGRS.2024.3429350
101. Mapping Dwellings in IDP/Refugee Settlements Using Deep Learning O. Ghorbanzadeh et al. 10.3390/rs14246382
102. Domain Adaptation for Mapping LCZs in Sub-Saharan Africa With Remote Sensing: A Comprehensive Approach to Health Data Analysis B. Rousse et al. 10.1109/JSTARS.2024.3421284
103. Super-Resolution of Remote Sensing Images for ×4 Resolution without Reference Images Y. Li et al. 10.3390/electronics11213474
104. High-Resolution Land Use Land Cover Dataset for Meteorological Modelling—Part 2: ECOCLIMAP-SG-ML an Ensemble Land Cover Map T. Rieutord et al. 10.3390/land13111875
105. SSGAN: Cloud removal in satellite images using spatiospectral generative adversarial network S. Ghildiyal et al. 10.1016/j.eja.2024.127333
106. Spatial and Spectral Translation of Landsat 8 to Sentinel-2 Using Conditional Generative Adversarial Networks R. Mukherjee & D. Liu 10.3390/rs15235502
107. SOSSF: Landsat-8 Image Synthesis on the Blending of Sentinel-1 and MODIS Data Y. Xia et al. 10.1109/TGRS.2024.3352662
108. Hybrid cGAN: Coupling Global and Local Features for SAR-to-Optical Image Translation Z. Wang et al. 10.1109/TGRS.2022.3212208
109. Structure similarity virtual map generation network for optical and SAR image matching S. Chen & L. Mei 10.3389/fphy.2024.1287050
110. SCT-CR: A synergistic convolution-transformer modeling method using SAR-optical data fusion for cloud removal J. Ma et al. 10.1016/j.jag.2024.103909
111. AMM-FuseNet: Attention-Based Multi-Modal Image Fusion Network for Land Cover Mapping W. Ma et al. 10.3390/rs14184458
112. A Combined Convolutional Neural Network for Urban Land-Use Classification with GIS Data J. Yu et al. 10.3390/rs14051128
113. Seeing Through Clouds in Satellite Images M. Zhao et al. 10.1109/TGRS.2023.3239592
114. Sen-2 LULC: Land use land cover dataset for deep learning approaches S. Sawant et al. 10.1016/j.dib.2023.109724
115. Reproducibility and Replicability in SAR Remote Sensing T. Balz & F. Rocca 10.1109/JSTARS.2020.3005912
116. Time-series surface water reconstruction method (TSWR) based on spatial distance relationship of multi-stage water boundaries M. Li et al. 10.1080/17538947.2022.2159553
117. Improving 3-m Resolution Land Cover Mapping through Efficient Learning from an Imperfect 10-m Resolution Map R. Dong et al. 10.3390/rs12091418
118. Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives X. Zhu et al. 10.1109/MGRS.2020.3046356
119. Deep Learning Methods for Semantic Segmentation in Remote Sensing with Small Data: A Survey A. Yu et al. 10.3390/rs15204987
120. Uncertainty-Based Human-in-the-Loop Deep Learning for Land Cover Segmentation C. García Rodríguez et al. 10.3390/rs12223836
121. Advances and Challenges in Multimodal Remote Sensing Image Registration B. Zhu et al. 10.1109/JMASS.2023.3244848
122. Self-Supervised Remote Sensing Feature Learning: Learning Paradigms, Challenges, and Future Works C. Tao et al. 10.1109/TGRS.2023.3276853
123. Land use land cover classification using Sentinel imagery based on deep learning models S. Sawant & J. Ghosh 10.1007/s12040-024-02298-z
124. WH-MAVS: A Novel Dataset and Deep Learning Benchmark for Multiple Land Use and Land Cover Applications J. Yuan et al. 10.1109/JSTARS.2022.3142898
125. Land Cover Classification in the Antioquia Region of the Tropical Andes Using NICFI Satellite Data Program Imagery and Semantic Segmentation Techniques L. Gomez-Ossa et al. 10.3390/data8120185
126. Self-Supervised Classification of SAR Images With Optical Image Assistance C. Li et al. 10.1109/TGRS.2023.3330826
127. Better, Not Just More: Data-centric machine learning for Earth observation R. Roscher et al. 10.1109/MGRS.2024.3470986
128. Efficient and Robust: A Cross-Modal Registration Deep Wavelet Learning Method for Remote Sensing Images D. Quan et al. 10.1109/JSTARS.2023.3276409
129. Meta-learning to address diverse Earth observation problems across resolutions M. Rußwurm et al. 10.1038/s43247-023-01146-0
130. Vision-Language Models in Remote Sensing: Current progress and future trends X. Li et al. 10.1109/MGRS.2024.3383473
131. Generalization Enhancement Strategies to Enable Cross-Year Cropland Mapping with Convolutional Neural Networks Trained Using Historical Samples S. Khallaghi et al. 10.3390/rs17030474
132. Cosine Similarity Template Matching Networks for Optical and SAR Image Registration W. Xiong et al. 10.1109/JSTARS.2024.3504555
133. Synthesis and evaluation of seamless, large-scale, multispectral satellite images using Generative Adversarial Networks on land use and land cover and Sentinel-2 data T. Dedring & A. Rienow 10.1080/15481603.2024.2364460
134. Multispectral Semantic Segmentation for Land Cover Classification: An Overview L. Thomas Ramos & A. Sappa 10.1109/JSTARS.2024.3438620
135. Detecting Canopy Gaps in Uneven-Aged Mixed Forests through the Combined Use of Unmanned Aerial Vehicle Imagery and Deep Learning N. Htun et al. 10.3390/drones8090484
136. Multiclass Land Cover Mapping from Historical Orthophotos Using Domain Adaptation and Spatio-Temporal Transfer Learning W. Van den Broeck et al. 10.3390/rs14235911
137. SAR-to-Optical Image Translation and Cloud Removal Based on Conditional Generative Adversarial Networks: Literature Survey, Taxonomy, Evaluation Indicators, Limits and Future Directions Q. Xiong et al. 10.3390/rs15041137
138. Interpretable Deep Learning Framework for Land Use and Land Cover Classification in Remote Sensing Using SHAP A. Temenos et al. 10.1109/LGRS.2023.3251652
139. Inter-satellite variability of grassland curing maps produced by different satellite sensors – Victoria, Australia S. Li 10.1080/17538947.2021.1900938
140. Time-Aware Dual LSTM Neural Network with Similarity Graph Learning for Remote Sensing Service Recommendation J. Zhang et al. 10.3390/s24041185
141. Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning G. Xu et al. 10.3390/rs14092263
142. Global perspectives on sand dune patterns: Scale-adaptable classification using Landsat imagery and deep learning strategies Z. Zheng et al. 10.1016/j.isprsjprs.2024.10.002
143. A Flexible Multi-Temporal and Multi-Modal Framework for Sentinel-1 and Sentinel-2 Analysis Ready Data P. Upadhyay et al. 10.3390/rs14051120
144. Multi-Label Remote Sensing Image Land Cover Classification Based on a Multi-Dimensional Attention Mechanism H. You et al. 10.3390/rs15204979
145. Amplitude SAR Imagery Splicing Localization E. Cannas et al. 10.1109/ACCESS.2022.3161836
146. Robust SAR-assisted cloud removal via supervised align-guided fusion and bidirectional hybrid reconstruction A. Wang et al. 10.1080/17538947.2025.2472909
147. Self-Supervised Learning in Remote Sensing: A review Y. Wang et al. 10.1109/MGRS.2022.3198244