Articles | Volume 13, issue 1
Earth Syst. Sci. Data, 13, 1–31, 2021
https://doi.org/10.5194/essd-13-1-2021
Earth Syst. Sci. Data, 13, 1–31, 2021
https://doi.org/10.5194/essd-13-1-2021

Data description paper 05 Jan 2021

Data description paper | 05 Jan 2021

An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018

Yongzhe Chen et al.

Viewed

Total article views: 4,116 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,049 983 84 4,116 318 76 118
  • HTML: 3,049
  • PDF: 983
  • XML: 84
  • Total: 4,116
  • Supplement: 318
  • BibTeX: 76
  • EndNote: 118
Views and downloads (calculated since 08 May 2020)
Cumulative views and downloads (calculated since 08 May 2020)

Viewed (geographical distribution)

Total article views: 3,414 (including HTML, PDF, and XML) Thereof 3,398 with geography defined and 16 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Sep 2021
Download
Short summary
Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By calibrating and combining 11 different products derived from satellite observation, we developed a new global surface soil moisture dataset spanning from 2003 to 2018 with high accuracy. Using this new dataset, not only can the global long-term trends be derived, but also the seasonal variation and spatial distribution of surface soil moisture at different latitudes can be better studied.