Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 17
Articles | Volume 18, issue 17
https://doi.org/10.5194/gmd-18-5513-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-5513-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 17
Development and technical paper
 | 
02 Sep 2025
Development and technical paper |  | 02 Sep 2025

Accurate and fast prediction of radioactive pollution by kriging coupled with auto-associative models

Raphaël Périllat, Sylvain Girard, and Irène Korsakissok

Viewed

Total article views: 4,107 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,400 579 128 4,107 146 224
  • HTML: 3,400
  • PDF: 579
  • XML: 128
  • Total: 4,107
  • BibTeX: 146
  • EndNote: 224
Views and downloads (calculated since 21 Feb 2025)
Cumulative views and downloads (calculated since 21 Feb 2025)

Viewed (geographical distribution)

Total article views: 4,107 (including HTML, PDF, and XML) Thereof 4,071 with geography defined and 36 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 19 May 2026
Download
Short summary
We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Read more
Share