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1 KM Grid Population Dataset of China


FU Jingying1,2JIANG Dong1HUANG Yaohuan1
1Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China2University of Chinese Academy of Sciences, Beijing, China

DOI:10.3974/geodb.2014.01.06.V1

Published:Jun. 2014

Visitors:11063       Data Files Downloaded:2659      
Data Downloaded:20106.81 MB      Citations:

Key Words:

China,GDP,Grid,Spatial data,2005,2010

Abstract:

Census data with the spatial scale of administrative district cannot reveal the spatial differences sufficiently. Meanwhile, this kind of statistical population data cannot be integrated and analyzed with most of other gridded geographic datasets. People in pixels provide an effective way to solve this problem. We established multivariate statistical models for population in 1 KM pixels based on the correlation relationships between population and land use types. The urban population density, traffic conditions, DEM and total amount control were used for model correction. Forty counties with township population data from east, west and middle of China were chose for precision verification. The errors of the spatial population data in these counties are between 4.5% and 13.6% and most of them are less than 10%.Browse

Foundation Item:

Chinese Academy of Sciences(2012): KZZD-EW-08-03

Data Citation:

FU Jingying,JIANG Dong,HUANG Yaohuan.2014.1 KM Grid Population Dataset of China ( PopulationGrid_China ) ,Global Change Research Data Publishing & Repository,DOI:10.3974/geodb.2014.01.06.V1

Data Product:

ID Data Name Data Size Operation
0Datapaper_PopulationGrid_China.pdf1282.00kbDownLoad
1 PopulationGrid_China2005.zip 7670.44kb DownLoad
2 PopulationGrid_China2010.zip 7800.77kb DownLoad
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum