Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3705-2024
© Author(s) 2024. 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-16-3705-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A 100 m gridded population dataset of China's seventh census using ensemble learning and big geospatial data
Yuehong Chen
CORRESPONDING AUTHOR
College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
Congcong Xu
College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
Yong Ge
CORRESPONDING AUTHOR
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiaoxiang Zhang
College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
Ya'nan Zhou
College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China
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- Comprehensive assessment of the recent dike breach at Dongting Lake Z. Zhang et al. 10.59717/j.xinn-geo.2024.100106
- Spatiotemporal correlations of PM2.5 and O3 variations: A street-scale perspective on synergistic regulation X. Lin et al. 10.1016/j.scitotenv.2025.178578
- Structure-aware deep learning network for building height estimation Y. Chen et al. 10.1016/j.jag.2025.104443
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- Risk assessment of seawater intrusion disaster based on FDAHP-EWM method in coastal region of Jinzhou City, China H. Li et al. 10.1080/10807039.2025.2470746
- Uncovering the drivers of gender inequality in perceptions of safety: An interdisciplinary approach combining street view imagery, socio-economic data and spatial statistical modelling Y. Zhu et al. 10.1016/j.jag.2024.104230
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Latest update: 18 Apr 2025
Short summary
Population data is crucial for human–nature interactions. Gridded population data can address limitations of census data in irregular units. In China, rapid urbanization necessitates timely and accurate population grids. However, existing datasets for China are either outdated or lack recent census data. Hence, a novel approach was developed to disaggregate China’s seventh census data into 100 m population grids. The resulting dataset outperformed the existing LandScan and WorldPop datasets.
Population data is crucial for human–nature interactions. Gridded population data can address...
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