Articles | Volume 13, issue 3
Earth Syst. Sci. Data, 13, 1385–1401, 2021
https://doi.org/10.5194/essd-13-1385-2021
Earth Syst. Sci. Data, 13, 1385–1401, 2021
https://doi.org/10.5194/essd-13-1385-2021

Data description paper 31 Mar 2021

Data description paper | 31 Mar 2021

Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019

Qiang Zhang et al.

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Cited articles

Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodriguez-Fernandez, N., and Wigneron, J.-P.: The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth Syst. Sci. Data, 9, 293–315, https://doi.org/10.5194/essd-9-293-2017, 2017. 
Chan, S. K., Bindlish, R., O'Neill, P., Jackson, T., Njoku, E., Dunbar, S., and Colliander, A.: Development and assessment of the SMAP enhanced passive soil moisture product, Remote Sens. Environ., 204, 931–941, https://doi.org/10.1016/j.rse.2017.08.025, 2018. 
Chen, J., Zhu, X., Vogelmann, J. E., Gao, F., and Jin, S.: A simple and effective method for filling gaps in Landsat ETM+ SLC-off images, Remote Sens. Environ., 115, 1053–1064, https://doi.org/10.1016/j.rse.2010.12.010, 2011. 
Chen, Y., Feng, X., and Fu, B.: 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, 2021. 
Cho, E., Su, C. H., Ryu, D., Kim, H., and Choi, M.: Does AMSR2 produce better soil moisture retrievals than AMSR-E over Australia?, Remote Sens. Environ., 188, 95–105, https://doi.org/10.1016/j.rse.2016.10.050, 2017. 
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Short summary
Acquired daily soil moisture products are always incomplete globally (just about 30 %–80 % coverage ratio) due to the satellite orbit coverage and the limitations of soil moisture retrieval algorithms. To solve this inevitable problem, we generate long-term seamless global daily (SGD) AMSR2 soil moisture productions from 2013 to 2019. These productions are significant for full-coverage global daily hydrologic monitoring, rather than averaging as the monthly–quarter–yearly results.