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Physical, Social, and Biological Attributes for Improved Understanding and Prediction of Wildfires: FPA FOD- 2 Attributes Dataset
  • +11
  • 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,
  • Mojtaba Sadegh
Yavar Pourmohamad
Department of Computer Science, Boise State University, Department of Civil Engineering, Boise State University
John T Abatzoglou
Management of Complex Systems Department, University of California
Erin J Belval
Erica Fleishman
College of Earth, Ocean, and Atmospheric Sciences, Oregon State University
Karen Short
Matthew C Reeves
Nicholas Nauslar
Bureau of Land Management
Philip E Higuera
Department of Ecosystem and Conservation Sciences, University of Montana
Eric Henderson
Department of Computer Science, Boise State University
Sawyer Ball
Department of Computer Science, Boise State University
Amir Aghakouchak
Department of Civil and Environmental Engineering, 11 United Nations University Institute for Water, Environment and Health, University of California
Jeffrey P Prestemon
Julia Olszewski
Mojtaba Sadegh
Bureau of Land Management, Department of Civil Engineering, Boise State University

Corresponding Author:[email protected]

Author Profile


Wildfires are increasingly impacting social and environmental systems in the United States. The ability to mitigate the adverse effects of wildfires increases with understanding of the social, physical, and biological conditions that co-occurred with or caused the wildfire ignitions and contributed to the wildfire impacts. To this end, we developed the FPA FOD-Attributes dataset, which augments the sixth version of the Fire Program Analysis-Fire Occurrence Database (FPA FOD v6) with nearly 270 attributes that coincide with the date and location of each wildfire ignition in the United States. FPA FOD v6 contains information on location, jurisdiction, discovery time, cause, and final size of >2.3 million wildfires from 1992-2020 in the United States. For each wildfire, we added physical (e.g., weather, climate, topography, infrastructure), biological (e.g., land cover, normalized difference vegetation index), social (e.g., population density, social vulnerability index), and administrative (e.g., national and regional preparedness level, jurisdiction) attributes. This publicly available dataset can be used to answer numerous questions about the covariates associated with human- and lightning-caused wildfires. Furthermore, the FPA FOD-Attributes dataset can support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including development of machine learning models.
19 Oct 2023Submitted to ESS Open Archive
19 Oct 2023Published in ESS Open Archive