Articles | Volume 1, issue 1
https://doi.org/10.5194/eo-1-155-2026
https://doi.org/10.5194/eo-1-155-2026
Research article
 | 
05 Nov 2026
Research article |  | 05 Nov 2026

A neural-network based observation operator for the assimilation of microwave satellite observations with LDAS-Monde on global cropland for improving land-surface variables

Jasmin Vural, Pierre Vanderbecken, Bertrand Bonan, Oscar Rojas-Muñoz, and Jean-Christophe Calvet

Viewed

Total article views: 1,183 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
658 423 102 1,183 86 127
  • HTML: 658
  • PDF: 423
  • XML: 102
  • Total: 1,183
  • BibTeX: 86
  • EndNote: 127
Views and downloads (calculated since 25 Feb 2026)
Cumulative views and downloads (calculated since 25 Feb 2026)

Viewed (geographical distribution)

Total article views: 1,183 (including HTML, PDF, and XML) Thereof 1,156 with geography defined and 27 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Nov 2026
Download
Short summary
New satellite observations are used to improve our understanding of agricultural land on a global scale. Innovative artificial intelligence methods are employed to combine the available information. This improvement is evaluated using independent observations and varies depending on the characteristics of instruments and models.
Share