AGGREGATING CLOUD-FREE SENTINEL-2 IMAGES WITH GOOGLE EARTH ENGINE

45 citations as recorded by crossref.

1. Influence of Image Compositing and Multisource Data Fusion on Multitemporal Land Cover Mapping of Two Philippine Watersheds N. Almarines et al.
2. Cloud Removal With SAR-Optical Data Fusion Using a Unified Spatial–Spectral Residual Network Y. Wang et al.
3. Multi-year mapping of cropping systems in regions with smallholder farms from Sentinel-2 images in Google Earth engine H. Qi et al.
4. Unsupervised multimodal thick cloud removal for optical remote sensing images via adversarial learning Q. Han et al.
5. Automatized Sentinel-2 mosaicking for large area forest mapping T. Pitkänen et al.
6. CERMF-Net: A SAR-Optical Feature Fusion for Cloud Elimination From Sentinel-2 Imagery Using Residual Multiscale Dilated Network J. Anandakrishnan et al.
7. Semi-Supervised Urban Change Detection Using Multi-Modal Sentinel-1 SAR and Sentinel-2 MSI Data S. Hafner et al.
8. Analysis of the Spatiotemporal Urban Expansion of the Rome Coastline through GEE and RF Algorithm, Using Landsat Imagery F. Lodato et al.
9. So2Sat LCZ42: A Benchmark Data Set for the Classification of Global Local Climate Zones [Software and Data Sets] X. Zhu et al.
10. Cloud-Guided Fusion With SAR-to-Optical Translation for Thick Cloud Removal X. Xiang et al.
11. A framework for large-scale mapping of human settlement extent from Sentinel-2 images via fully convolutional neural networks C. Qiu et al.
12. Urban sprawl characterization and its impact on peri-urban agriculture in Sidi Bel Abbes, Algeria, using multi-date landsat imagery D. Mansour et al.
13. Dense NDVI Time Series by Fusion of Optical and SAR-Derived Data T. Roßberg & M. Schmitt
14. Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning Y. Li et al.
15. 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.
16. A robust and fully automated morphology-based approach for revealing changes of China’s coastal tidal flats from 2016 to 2024 L. Cheng et al.
17. Thick Cloud Removal Using Cloud Mask-Guided SAR-Optical Fusion Network S. Meng et al.
18. Agricultural Land Classification Using Vegetation Indices, PCA, and Google Earth Engine: Case Study of Söke/Aydın M. İNALPULAT et al.
19. Unsupervised Deep Joint Segmentation of Multitemporal High-Resolution Images S. Saha et al.
20. DKDFN: Domain Knowledge-Guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classification Y. Li et al.
21. Fusing Multiseasonal Sentinel-2 Imagery for Urban Land Cover Classification With Multibranch Residual Convolutional Neural Networks C. Qiu et al.
22. RTFormer: radiative transfer model-coupled transformer for cloud removal in optical remote sensing imagery S. Meng et al.
23. The Green Revolution from space: Mapping the historic dynamics of main rice types in one of the world's food bowls J. Peña-Arancibia et al.
24. Cloud Removal with SAR-Optical Data Fusion and Graph-Based Feature Aggregation Network S. Chen et al.
25. Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation S. Praticò et al.
26. On the interchangeability of Landsat and MODIS data in the CMRSET actual evapotranspiration model – Comment on “Monitoring irrigation using Landsat observations and climate data over regional scales in the Murray-Darling Basin” by David Bretreger, In-Young Yeo, Greg Hancock and Garry Willgoose J. Peña-Arancibia et al.
27. Leveraging Sentinel-2 A time series and integrated cellular automata-deep learning for accurate land cover forecasts in Northern Iraq F. Hussein et al.
28. Contributions to Satellite-Based Land Cover Classification, Vegetation Quantification and Grassland Monitoring in Central Asian Highlands Using Sentinel-2 and MODIS Data H. Zandler et al.
29. FCFNet: A Frequency-Domain-Guided Cross-Modal Feature Fusion Network for Cloud Removal C. Wu et al.
30. A High-Resolution Dataset for Arabica Coffee Distribution in Yunnan, Southwestern China H. Shan et al.
31. Land consumption in cities: A comparative study across the globe J. Hu et al.
32. So2Sat POP - A Curated Benchmark Data Set for Population Estimation from Space on a Continental Scale S. Doda et al.
33. HF-T2CR: High-Fidelity Thin and Thick Cloud Removal in Optical Satellite Images Through SAR Fusion X. Li et al.
34. Estimación de la producción de cebada a partir de imágenes Sentinel-1, Sentinel-2 y variables climáticas C. Iranzo et al.
35. High-spatial-resolution surface soil moisture retrieval using the Deep Forest model in the cloud environment over the Tibetan Plateau Z. Li et al.
36. Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China R. Yang et al.
37. Potential of Large-Scale Inland Water Body Mapping from Sentinel-1/2 Data on the Example of Bavaria’s Lakes and Rivers M. Schmitt
38. Cloud removal for optical remote sensing imagery using the SPA-CycleGAN network R. Jing et al.
39. GLAMOUR: GLobAl building MOrphology dataset for URban hydroclimate modelling R. Li et al.
40. Modelling and mapping growing stock volume in small-scale forest plantations using Sentinel-2 remotely sensed data E. Mauya et al.
41. Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion A. Meraner et al.
42. Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery S. Peters et al.
43. Deep learning-based local climate zone classification using Sentinel-1 SAR and Sentinel-2 multispectral imagery L. Zhou et al.
44. Data-interactive mamba driven SAR-optical fusion cloud removal F. Liu et al.
45. Cross-Modal Hierarchical Fusion Framework for Classifying Heterogeneous Spatial Patterns in Local Climate Zone Mapping C. Su et al.