Articles | Volume 15, issue 6
https://doi.org/10.5194/essd-15-2347-2023
https://doi.org/10.5194/essd-15-2347-2023
Data description paper
 | 
07 Jun 2023
Data description paper |  | 07 Jun 2023

An improved global land cover mapping in 2015 with 30 m resolution (GLC-2015) based on a multisource product-fusion approach

Bingjie Li, Xiaocong Xu, Xiaoping Liu, Qian Shi, Haoming Zhuang, Yaotong Cai, and Da He

Related authors

Dynamics of China’s Forest Carbon Storage: The First 30 m Annual Aboveground Biomass Mapping from 1985 to 2023
Yaotong Cai, Peng Zhu, Xing Li, Xiaoping Liu, Yuhe Chen, Qianhui Shen, Xiaocong Xu, Honghui Zhang, Sheng Nie, Cheng Wang, Jia Wang, Bingjie Li, Changjiang Wu, and Haoming Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-96,https://doi.org/10.5194/essd-2025-96, 2025
Preprint under review for ESSD
Short summary

Related subject area

Domain: ESSD – Land | Subject: Land Cover and Land Use
U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling
Yifan Cheng, Lei Zhao, TC Chakraborty, Keith Oleson, Matthias Demuzere, Xiaoping Liu, Yangzi Che, Weilin Liao, Yuyu Zhou, and Xinchang “Cathy” Li
Earth Syst. Sci. Data, 17, 2147–2174, https://doi.org/10.5194/essd-17-2147-2025,https://doi.org/10.5194/essd-17-2147-2025, 2025
Short summary
The Earth Topography 2022 (ETOPO 2022) global DEM dataset
Michael MacFerrin, Christopher Amante, Kelly Carignan, Matthew Love, and Elliot Lim
Earth Syst. Sci. Data, 17, 1835–1849, https://doi.org/10.5194/essd-17-1835-2025,https://doi.org/10.5194/essd-17-1835-2025, 2025
Short summary
The 20 m Africa rice distribution map of 2023
Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Mingyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang
Earth Syst. Sci. Data, 17, 1781–1805, https://doi.org/10.5194/essd-17-1781-2025,https://doi.org/10.5194/essd-17-1781-2025, 2025
Short summary
A 30m resolution annual cropland extent dataset of Africa in recent decades of the 21st century
Zihang Lou, Dailiang Peng, Zhou Shi, Hongyan Wang, Yaqiong Zhang, Xue Yan, Zhongxing Chen, Su Ye, Le Yu, Jinkang Hu, Yulong Lv, Hao Peng, Yizhou Zhang, and Bing Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-133,https://doi.org/10.5194/essd-2025-133, 2025
Revised manuscript accepted for ESSD
Short summary
Revised and updated geospatial monitoring of 21st century forest carbon fluxes
David A. Gibbs, Melissa Rose, Giacomo Grassi, Joana Melo, Simone Rossi, Viola Heinrich, and Nancy L. Harris
Earth Syst. Sci. Data, 17, 1217–1243, https://doi.org/10.5194/essd-17-1217-2025,https://doi.org/10.5194/essd-17-1217-2025, 2025
Short summary

Cited articles

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. 
Bartholomé, E. and Belward, A. S.: GLC2000: A new approach to global land cover mapping from Earth observation data, Int. J. Remote Sens., 26, 1959–1977, https://doi.org/10.1080/01431160412331291297, 2005. 
Bounoua, L., DeFries, R., Collatz, G. J., Sellers, P., and Khan, H.: Effects of land cover conversion on surface climate, Climatic Change, 52, 29–64, https://doi.org/10.1023/A:1013051420309, 2002. 
Bunting, P., Rosenqvist, A., Lucas, R. M., Rebelo, L.-M., Hilarides, L., Thomas, N., Hardy, A., Itoh, T., Shimada, M., and Finlayson, C. M.: The Global Mangrove Watch-A new 2010 global baseline of mangrove extent, Remote Sens., 10, 1669,https://doi.org/10.3390/rs10101669, 2018. 
Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R. M., Thomas, N., Tadono, T., Worthington, T. A., Spalding, M., Murray, N. J., and Rebelo, L.-M.: Global mangrove extent change 1996-2020: Global Mangrove Watch version 3.0, Remote Sens., 14, 3657, https://doi.org/10.3390/rs14153657, 2022. 
Download
Short summary
A global land cover map with fine spatial resolution is important for climate and environmental studies, food security, or biodiversity conservation. In this study, we developed an improved global land cover map in 2015 with 30 m resolution (GLC-2015) by fusing the existing land cover products based on the Dempster–Shafer theory of evidence on the Google Earth Engine platform. The GLC-2015 performed well, with an OA of 79.5 % (83.6 %) assessed with the global point-based (patch-based) samples.
Share
Altmetrics
Final-revised paper
Preprint