This dataset comprises three periods (2000, 2010, and 2020) of county-level population census spatial distribution raster data for the Yellow River Basin. Based on the fifth, sixth, and seventh national population censuses at the county level, the Excel-formatted population data were first vectorized. These vector data were then combined with land use information to perform rasterization processing through a zonal density mapping model. Population density values were allocated to 1 km resolution cells, ultimately generating continuous population distribution rasters. All datasets were projected into the CGCS2000 Albers coordinate system. The data include population density rasters from three distinct time periods, covering the entire Yellow River Basin with a temporal interval of 10 years and a spatial resolution of 1 km.
The Fifth, Sixth, and Seventh National Census Data at the District and County Levels.
Based on county-level population data from the Fifth, Sixth, and Seventh National Censuses of China, combined with vectorized administrative boundary data of county-level divisions and calculated based on administrative area, three periods (2000, 2010, and 2020) of county-level population density were obtained. Subsequently, using contemporaneous land use data as spatial reference, a zonal density mapping model was applied to rasterize the county-level vector data through gridding processing, thereby assigning population density values to 1 km × 1 km cells and generating continuous population distribution rasters. Finally, all raster datasets were uniformly transformed into the CGCS2000 Albers projection coordinate system to standardize data formats and spatial references, resulting in the final spatial distribution dataset of county-level census population data for the Yellow River Basin across the three periods (2000, 2010, and 2020).
The data presented in this study originate from the Fifth, Sixth, and Seventh National Census conducted at the district and county levels in China during 2000, 2010, and 2020 respectively, reflecting the spatial distribution patterns of population at corresponding time points.
| # | number | name | type |
| 1 | 2023NCDC004 | NCDC Open Fund Project |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.NIEER.DB7079.2026
10.12072/ncdc.nieer.db7079.2026
