Articles | Volume 23, issue 9
https://doi.org/10.5194/nhess-23-2937-2023
https://doi.org/10.5194/nhess-23-2937-2023
Research article
 | 
06 Sep 2023
Research article |  | 06 Sep 2023

Fire risk modeling: an integrated and data-driven approach applied to Sicily

Alba Marquez Torres, Giovanni Signorello, Sudeshna Kumar, Greta Adamo, Ferdinando Villa, and Stefano Balbi

Viewed

Total article views: 3,390 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,677 621 92 3,390 173 123 124
  • HTML: 2,677
  • PDF: 621
  • XML: 92
  • Total: 3,390
  • Supplement: 173
  • BibTeX: 123
  • EndNote: 124
Views and downloads (calculated since 20 Feb 2023)
Cumulative views and downloads (calculated since 20 Feb 2023)

Viewed (geographical distribution)

Total article views: 3,390 (including HTML, PDF, and XML) Thereof 3,252 with geography defined and 138 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Mar 2026
Download
Short summary
Only by mapping fire risks can we manage forest and prevent fires under current and future climate conditions. We present a fire risk map based on k.LAB, artificial-intelligence-powered and open-source software integrating multidisciplinary knowledge in near real time. Through an easy-to-use web application, we model the hazard with 84 % accuracy for Sicily, a representative Mediterranean region. Fire risk analysis reveals 45 % of vulnerable areas face a high probability of danger in 2050.
Share
Altmetrics
Final-revised paper
Preprint