References：
[1] Zhang, C. X. Using latitude and longitude grid cells to compile a population density map: Taking the Beijing-Tianjin-Tangshan area as an example [J]. Areal Research and Development, 1985, 4(2): 57-66.
[2] Hu, H. Y. The distribution, regionalization and prospect of China's population [J]. Acta Geographica Sinica, 1990, 45 (2): 139-145.
[3] Wu, J. G. Landscape Ecology: Pattern Process Scale and Hierarchy (2nd Edition) [M]. Beijing: Higher Education Press, 2007: 147-154.
[4] Zheng, D., Ou Y., Zhou, C. H. Understanding of and thinking over geographical regionalization methodology [J]. Acta Geographica Sinica, 2008, 63(6): 563-573.
[5] Hebei Population and Family Planning Commission. Research Report on the Functional Area of Population Development in Hebei Province [M]. Shijiazhuang: Hebei People's Publishing House, 2009.
[6] Liu, J. S. The geographical meaning about the modifiable areal unit problem in the population density scaling [D]. Shijiazhuang: Hebei Normal University, 2009.
[7] Stevens, F. R., Gaughan, A. E., Linard, C., et al. Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data [J]. Plos One, 2015, 10(2): e0107042.
[8] Gaughan, A. E., Stevens, F. R., Huang, Z. J., et al. Spatiotemporal patterns of population in mainland China, 1990 to 2010 [J]. Scientific Data, 2016, 3: 160005.
[9] Tatem, A. J. WorldPop, open data for spatial demography [J]. Scientific Data, 2017, 4: 170004.
[10] Tan, M., Liu, K., Liu, Lin., et al. Spatialization of population in the Pearl River Delta in 30 m grids using random forest model [J]. Progress in Geography, 2017, 36(10): 1304-1312.
[11] Feng, X, T. Social Research Methods (5th Edition) [M]. Beijing: China Renmin University Press, 2018: 75-78.
[12] Wardrop, N. A., Jochem, W. C., Bird, T. J., et al. Spatially disaggregated population estimates in the absence of national population and housing census data [J]. PNAS, 2018, 115(14): 3529-3537.
[13] Wang, C., Kan, A. K., Zeng, Y. L., et al. Population distribution pattern and influencing factors in Tibet based on random forest model [J]. Acta Geographica Sinica, 2019, 74(4): 664-680.
[14] Wang, Z., Xia, H. B., Tian, Y., et al. Big data analysis on the existence of Hu Huanyong Line: Ecological and new economic geography understanding of China's population distribution characteristics [J]. Acta Ecologica Sinica, 2019, 39(14): 5166-5177.
[15] Ye, T. T., Zhao, N. Z., Yang, X. C., et al. Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model [J]. Science of the Total Environment, 2019, 658: 936-946.
[16] Leyk, S., Gaughan, A. E., Adamo, S. B., et al. The spatial allocation of population: A review of large-scale gridded population data products and their fitness for use [J]. Earth System Science Data, 2019, 11(3): 1385-1409.
[17] Liu, Y., Yang, X. J., Liu, J. S. Experimental study on optimization of population density models based on random forest [J]. Global Change Research Data Publishing & Repository, 2020, 4(4): 402-416.
[18] Li, L. L., Liu, J. S., Li, Z., et al. Experimental study of population density using an optimized random forest model [J]. Acta Geographica Sinica, 2023, 78(5): 1304-1320.