Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 7
Articles | Volume 17, issue 7
https://doi.org/10.5194/gmd-17-2987-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-2987-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 7
Model description paper
 | 
16 Apr 2024
Model description paper |  | 16 Apr 2024

Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation

Mohamad Hakam Shams Eddin and Juergen Gall

Viewed

Total article views: 2,579 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,923 586 70 2,579 65 107
  • HTML: 1,923
  • PDF: 586
  • XML: 70
  • Total: 2,579
  • BibTeX: 65
  • EndNote: 107
Views and downloads (calculated since 07 Nov 2023)
Cumulative views and downloads (calculated since 07 Nov 2023)

Viewed (geographical distribution)

Total article views: 2,579 (including HTML, PDF, and XML) Thereof 2,555 with geography defined and 24 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 02 Nov 2025
Download
Short summary
In this study, we use deep learning and a climate simulation to predict the vegetation health as it would be observed from satellites. We found that the developed model can help to identify regions with a high risk of agricultural drought. The main applications of this study are to estimate vegetation products for periods where no satellite data are available and to forecast the future vegetation response to climate change based on climate scenarios.
Read more
Share