Data for:Improved Population Mapping for China Using the 3D Build-ing, Nighttime Light, Points-of-interest, and Land Use/Cover Data Within a Multiscale Geographically Weighted Regression Model

Auxiliary Data.gdb:
Land_use: original land use data
POI_name: interests-point-data from the Amap platform (name indicates category)

New_gridded_population_dataset(.gdb): experimental result data, i.e., a gridded population map of mainland China with a resolution of 100 meters

New_minus_WorldPop_PopulationResidual(.gdb): pixel-level residuals of the new gridded population dataset with the Worldpop dataset

PopulationData_AdministrativeUnitLevel.gdb:
Population_data_mainlandChina_level3: population data at the district and county level in mainland China
Population_data_Name_level4_Table: township and street-level population data for provinces and municipalities

POI_Correlation_Coefficient:
Python script: programming implementation for selecting the optimal bandwidth for POI
Zonal statistical output of POI kernel density values: summary of various POI kernel densities in residential areas of administrative units
Summary of POI Pearson correlation coefficients: sum of Pearson's correlation coefficients for 13 types of POIs at a certain bandwidth

Note:
Due to the storage space limitation, 3D building, nighttime light, and WorldPop datasets have not been uploaded. To access these publicly available data, please visit the official website via the "Related links" at the bottom. In addition, we are not authorized to share data for the fourth level of administrative boundaries, so we only share the corresponding population data in tabular form.