Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-3045-2024
https://doi.org/10.5194/essd-16-3045-2024
Data description paper
 | 
28 Jun 2024
Data description paper |  | 28 Jun 2024

Physical, social, and biological attributes for improved understanding and prediction of wildfires: FPA FOD-Attributes dataset

Yavar Pourmohamad, John T. Abatzoglou, Erin J. Belval, Erica Fleishman, Karen Short, Matthew C. Reeves, Nicholas Nauslar, Philip E. Higuera, Eric Henderson, Sawyer Ball, Amir AghaKouchak, Jeffrey P. Prestemon, Julia Olszewski, and Mojtaba Sadegh

Viewed

Total article views: 882 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
658 169 55 882 68 42 38
  • HTML: 658
  • PDF: 169
  • XML: 55
  • Total: 882
  • Supplement: 68
  • BibTeX: 42
  • EndNote: 38
Views and downloads (calculated since 09 Nov 2023)
Cumulative views and downloads (calculated since 09 Nov 2023)

Viewed (geographical distribution)

Total article views: 882 (including HTML, PDF, and XML) Thereof 857 with geography defined and 25 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Jul 2024
Download
Short summary
The FPA FOD-Attributes dataset provides > 300 biological, physical, social, and administrative attributes associated with > 2.3×106 wildfire incidents across the US from 1992 to 2020. The dataset can be used to (1) answer numerous questions about the covariates associated with human- and lightning-caused wildfires and (2) support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models.
Altmetrics
Final-revised paper
Preprint