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1. Yao, P.P., Lu, H., Zhao, T.J., Wu, S.L., Shi, J.C., Yang K., Cosh, M.H., Zhang, P. (2022). A global daily soil moisture dataset derived from Chinese FengYun-3B Microwave Radiation Imager (MWRI) (2010-2019) . Scientific Data. (Under Review)( 查看 | Bibtex格式) 2. Yao, P.P., Lu, H., Shi, J.C., Zhao, T.J., Yang K., Cosh, M.H., Gianotti, D.J.S., & Entekhabi, D. (2021). A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019). Scientific Data, 8, 143 (2021). https://doi.org/10.1038/s41597-021-00925-8( 查看 | Bibtex格式) 3. Yao, P.P., Shi, J.C., Zhao, T.J., Lu, H. & Al-Yaari, A. (2017). Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopting the Microwave Vegetation Index. Remote Sensing 9(1), 35.( 查看 | Bibtex格式)
Yao, P.P., Lu, H., Shi, J.C., Zhao, T.J., Yang K., Cosh, M.H., Gianotti, D.J.S., & Entekhabi, D. (2021). A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019). Scientific Data, 8, 143 (2021). https://doi.org/10.1038/s41597-021-00925-8
Xie, Pingping; Joyce, Robert; Wu, Shaorong; Yoo, S.-H.; Yarosh, Yelena; Sun, Fengying; Lin, Roger, NOAA CDR Program (2019): NOAA Climate Data Record (CDR) of CPC Morphing Technique (CMORPH) High Resolution Global Precipitation Estimates, Version 1 [indicate subset]. NOAA National Centers for Environmental Information. https://doi.org/10.25921/w9va-q159 [access date]
Youngryel Ryu, Chongya Jiang, Hideki Kobayashi, Matteo Detto,MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5km resolution from 2000,Remote Sensing of Environment,Volume 204, 2018,Pages 812-825,ISSN 0034-4257,https://doi.org/10.1016/j.rse.2017.09.021.
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.
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