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
Yavar Pourmohamad
Department of Civil Engineering, Boise State University, Boise, ID, USA
Department of Computer Science, Boise State University, Boise, ID, USA
John T. Abatzoglou
Management of Complex Systems Department, University of California, Merced, CA, USA
Erin J. Belval
USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, USA
Erica Fleishman
College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA
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.
The FPA FOD-Attributes dataset provides > 300 biological, physical, social, and administrative...
