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Optimized Model Based on Random Forest Application on Population Density Dataset: Taking Shijiazhuang as an Example (2007)

LI Lingling1LIU Jinsong*1,2,3,4LI Zhi1,2,3,4WEN Peizhang1LI Yancheng1LIU Yi1
1 School of Geographical Sciences,Hebei Normal University,Shijiazhuang 050024,China2 Hebei Technology Innovation Center for Remote Sensing Identification of Environmental Change,Shijiazhuang 050024,China3 GeoComputation and Planning Center of Hebei Normal University,Shijiazhuang 050024,China4 Hebei Key Laboratory of Environmental Change and Ecological Construction,Shijiazhuang 050024,China


Published:May 2024

Visitors:938       Data Files Downloaded:34      
Data Downloaded:4496.79 MB      Citations:

Key Words:

population density,random forest model,Shijiazhuang,grid


Based on the aggregated registered population data of Shijiazhuang as of 24:00 on April 30, 2007, the authors applied the optimized random forest model for population density to obtain the population density grid dataset for Shijiazhuang (SJZ_POP_2007). The SJZ_POP_2007 dataset includes the following data from 8 groups: (1) predicted population density data for Shijiazhuang (Predict_Data); (2) population density data for Shijiazhuang (Result_Data). Validity testing was conducted at the township level, and the goodness of fit (R2) of the result data reached 0.967. The SJZ_POP_2007 dataset has a spatial resolution of 100 m. The dataset is archived in .tif format, and consists of 64 data files with data size of 279 MB (compressed into one file, 132 MB). The related paper was published in Acta Geographica Sinica, Vol. 78, No. 5, 2023.

Foundation Item:

National Natural Science Foundation of China (42071167, 42201197, 40871073); Natural Science Foundation of Hebei Province (D2007000272); Hebei Normal University (L2024ZD07)

Data Citation:

LI Lingling, LIU Jinsong*, LI Zhi, WEN Peizhang, LI Yancheng, LIU Yi. Optimized Model Based on Random Forest Application on Population Density Dataset: Taking Shijiazhuang as an Example (2007)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024.


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Data Product:

ID Data Name Data Size Operation
1 SJZ_POP_2007.rar 135432.61KB