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Bright, E. A., Rose, A. N., Urban, M. L., & McKee, J. (2018). LandScan 2017 high-resolution global population data set (No. LandScan 2017 High-Resolution Global Population Da; 005854MLTPL00). Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States).
Center for International Earth Science Information Network - CIESIN - Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density Adjusted to Match 2015 Revision UN WPP Country Totals, Revision 11. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4F47M65. Accessed 2022/09/30
Du, J. and J. S. Kimball. (2021). Daily Global Land Parameters Derived from AMSR-E and AMSR2, Version 3 [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/WPXUQ72A4484. Date Accessed 09-27-2022.
Rodell, M., P.R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J.K. Entin, J.P. Walker, D. Lohmann, and D. Toll, 2004: The Global Land Data Assimilation System, Bull. Amer. Meteor. Soc., 85, 381-394, doi:10.1175/BAMS-85-3-381
Du J, Jones L A, Kimball J S. Daily Global Land Parameters Derived from AMSR-E and AMSR2, Version 2[J]. 2017.
Dobson, J. E., Bright, E. A., Coleman, P. R., Durfee, R. C., & Worley, B. A. (2000). LandScan: a global population database for estimating populations at risk. Photogrammetric engineering and remote sensing, 66(7), 849-857.
Chen, Y., Feng, X., & Fu, B. (2021). An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018, Earth Syst. Sci. Data, 13, 1–31, https://doi.org/10.5194/essd-13-1-2021
Doxsey-Whitfield, E., MacManus, K., Adamo, S. B., Pistolesi, L., Squires, J., Borkovska, O., & Baptista, S. R. (2015). Taking advantage of the improved availability of census data: a first look at the gridded population of the world, version 4. Papers in Applied Geography, 1(3), 226-234.
Brecht M , Miralles D G , Hans L , et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture[J]. Geoscientific Model Development Discussions, 2016:1-36.
Liang Gao, Dongdong Song, Yitao Yang, Changxing Xu, & Xiaobao Yang. (2021). District/County Level Population Census GIS Datasets in China (1953-2010) (Version V1) [Data set]. Science Data Bank. https://doi.org/10.11922/sciencedb.j00001.00273
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