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

Data sets

Physical, Social, and Biological Attributes for Improved Understanding and Prediction of Wildfires: FPA FOD-Attributes Dataset Yavar Pourmohamad et al. https://doi.org/10.5281/zenodo.8381129

Model code and software

FPA FOD-Attributes Python Codes Yavar Pourmohamad https://github.com/YavarPourmohamad/FPA-FOD.git

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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.
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