Articles | Volume 17, issue 8
https://doi.org/10.5194/essd-17-4039-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-4039-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
21 Aug 2025
Data description article |
| 21 Aug 2025
| 21 Aug 2025
GLC_FCS10: a global 10 m land-cover dataset with a fine classification system from Sentinel-1 and Sentinel-2 time-series data in Google Earth Engine
Xiao Zhang
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
Tingting Zhao
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China
Wenhan Zhang
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
Linlin Guan
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
Ming Bai
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
Xidong Chen
Future Urbanity & Sustainable Environment (FUSE) Lab, the University of Hong Kong, Hong Kong, 999007, China
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Total article views: 5,837 (including HTML, PDF, and XML)
Thereof 5,834 with geography defined
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Total article views: 4,489 (including HTML, PDF, and XML)
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- Improved land mask for satellite remote sensing of oceans and inland waters K. Mikelsons & M. Wang https://doi.org/10.5194/essd-18-231-2026
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- UTCMapper for 0.3 m urban tree canopy mapping: A case study in Shanghai S. Zhang et al. https://doi.org/10.1016/j.rse.2026.115435
- Development of island-specific land-use classification system and spatiotemporal pattern evolution analysis using Landsat time series for coastal zone management: A case study of Zhoushan Archipelago, China T. Ren et al. https://doi.org/10.1016/j.ecolind.2025.114158
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- Species information in multi-temporal Sentinel-2 data improves forest canopy height estimation C. Choi et al. https://doi.org/10.1016/j.agrformet.2026.111114
- DB-CRNet: A novel weakly supervised framework for Cross-Resolution land cover classification S. Wang et al. https://doi.org/10.1016/j.jag.2026.105332
- Assessing Optical, SAR, and Topographic Synergy for LULC Mapping in Cloud-Prone Mountain Environments Using a Systematic Ablation Design K. Escalona et al. https://doi.org/10.3390/geomatics6030045
- A 10 m High-precision Canopy Height Product for Nanping City, Fujian Province, China L. Yi et al. https://doi.org/10.1038/s41597-026-06767-6
- Cooling Intensity of Urban Blue–Green Spaces and Its Driving Mechanisms in the Yangtze River Delta Urban Agglomeration L. Gu & Z. Yue https://doi.org/10.3390/app16052165
- GlobalGeoTree: a multi-granular vision-language dataset for global tree species classification Y. Mu et al. https://doi.org/10.5194/essd-18-1379-2026
- A Scalable GEOBIA Framework for Urban Landscape Monitoring with Sentinel-2 Data: A Case Study in Hue City, Vietnam M. Choudhury et al. https://doi.org/10.3390/earth7020051
- Vegetation Mapping in Heterogeneous Forest–Shrub–Grass Ecosystems Using Fused High-Resolution Optical and SAR Data Q. Pang et al. https://doi.org/10.3390/rs18091373
- Delineating the Distribution Outline of Populus euphratica in the Mainstream Area of the Tarim River Using Multi-Source Thematic Classification Data H. Li et al. https://doi.org/10.3390/rs18010157
- Mapping Multi-Temporal Heat Risks Within the Local Climate Zone Framework: A Case Study of Jinan’s Main Urban Area, China Z. Ren et al. https://doi.org/10.3390/buildings15193619
- HSRRSFPD and MEGRDNet: empowering high-resolution farmland parcel mapping in complex terrains Y. Yan et al. https://doi.org/10.1016/j.jag.2026.105346
- Hybrid wetland city map: Improved wetland characterization through the synergy of global land cover products X. Yin et al. https://doi.org/10.1016/j.jag.2025.104994
- Benchmark Datasets for Satellite Image Time Series Classification: A Review A. Zhang et al. https://doi.org/10.3390/rs18101581
- Land cover mapping of China based on an improved bi-temporal comprehensive change detection method from Landsat MSS observations W. Ai et al. https://doi.org/10.1080/17538947.2025.2597065
- Spatial and Data-Driven Approaches for Mitigating Urban Heat in Coastal Cities K. Li & H. Wang https://doi.org/10.3390/buildings15193544
- Quantifying evapotranspiration and shading cooling of urban vegetation across climates under extreme heat using an integrated SCOPE-SEB model and surface temperature analysis Z. Yu et al. https://doi.org/10.1016/j.rse.2026.115343
- Land Use/Land Cover Remote Sensing Classification in Complex Subtropical Karst Environments: Challenges, Methodological Review, and Research Frontiers D. Huang et al. https://doi.org/10.3390/app15179641
- Potential of dynamic features derived from temporally dense Sentinel-1/2 imagery for improved floodplain wetland mapping X. Xiong et al. https://doi.org/10.1177/03091333261434476
Saved (final revised paper)
Latest update: 30 May 2026
Short summary
This work describes a novel global 10 m land-cover dataset with a fine classification system, which contains 30 land-cover subcategories and achieves sufficient performance on a global scale.
This work describes a novel global 10 m land-cover dataset with a fine classification system,...
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