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

Chen, Yongzhe; Feng, Xiaoming; Fu, Bojie

doi:https://doi.org/10.5194/essd-13-1-2021

Articles | Volume 13, issue 1

https://doi.org/10.5194/essd-13-1-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-13-1-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 1

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, Xiaoming Feng, and Bojie Fu

Supplement

https://doi.org/10.5194/essd-13-1-2021-supplement

Data sets

A new dataset of satellite observation-based global surface soil moisture covering 2003-2018 Yongzhe Chen https://doi.org/10.1594/PANGAEA.912597

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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.