Articles | Volume 17, issue 8
https://doi.org/10.5194/essd-17-4039-2025
https://doi.org/10.5194/essd-17-4039-2025
Data description paper
 | 
21 Aug 2025
Data description paper |  | 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, Liangyun Liu, Tingting Zhao, Wenhan Zhang, Linlin Guan, Ming Bai, and Xidong Chen

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Cited articles

Azzari, G. and Lobell, D. B.: Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring, Remote Sens. Environ., 202, 64–74, https://doi.org/10.1016/j.rse.2017.05.025, 2017. 
Ban, Y., Gong, P., and Giri, C.: Global land cover mapping using Earth observation satellite data: Recent progresses and challenges, ISPRS J. Photogramm., 103, 1–6, https://doi.org/10.1016/j.isprsjprs.2015.01.001, 2015. 
Belgiu, M. and Drăguţ, L.: Random forest in remote sensing: A review of applications and future directions, ISPRS J. Photogramm., 114, 24–31, https://doi.org/10.1016/j.isprsjprs.2016.01.011, 2016. 
Berger, M., Moreno, J., Johannessen, J. A., Levelt, P. F., and Hanssen, R. F.: ESA's sentinel missions in support of Earth system science, Remote Sens. Environ., 120, 84–90, https://doi.org/10.1016/j.rse.2011.07.023, 2012. 
Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., and Hostert, P.: Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany, Remote Sens. Environ., 269, 112831, https://doi.org/10.1016/j.rse.2021.112831, 2022. 
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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.
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