Articles | Volume 26, issue 13
https://doi.org/10.5194/hess-26-3337-2022
https://doi.org/10.5194/hess-26-3337-2022
Research article
 | 
04 Jul 2022
Research article |  | 04 Jul 2022

Exploring the combined use of SMAP and Sentinel-1 data for downscaling soil moisture beyond the 1 km scale

Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms

Viewed

Total article views: 3,189 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,102 1,010 77 3,189 179 47 64
  • HTML: 2,102
  • PDF: 1,010
  • XML: 77
  • Total: 3,189
  • Supplement: 179
  • BibTeX: 47
  • EndNote: 64
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads (calculated since 27 Oct 2021)

Viewed (geographical distribution)

Total article views: 3,189 (including HTML, PDF, and XML) Thereof 3,056 with geography defined and 133 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 22 Nov 2024
Download
Short summary
The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.