A newly enhanced database is expected to revolutionize wildfire prediction efforts by incorporating hundreds of additional factors that influence the ignition and spread of fires. The Fire Program Analysis Fire-Occurrence Database, developed by the U.S. Forest Service in 2013 and subsequently updated five times, now includes new environmental and social factors like topography, vegetation, social vulnerability, and economic justice metrics. With the addition of nearly 270 additional attributes, the database now contains information on 2.3 million fires in the United States from 1992 to 2020, providing greater insight into the individual and compounded impacts of these factors on wildfires.
The database’s expansion enables a deeper understanding of the unequal effects of wildfires on various human populations and ecosystems, which can help inform efforts to reduce inequities. By incorporating data from the database into artificial intelligence and machine learning models, researchers can gain insights into the drivers of past fires and project the likelihoods or effects of future fires. This information can be valuable for on-the-ground firefighters and managers as well as for power companies making decisions about implementing public safety power shutoffs or land management agencies deciding on land access restrictions during certain times of year.
The enhanced database is expected to be a valuable tool for policymakers and decision-makers who can now rely on objective evidence when making decisions related to wildfire preparedness and prevention. By moving away from intuition and emotions, policymakers can use data-driven insights to guide policies and actions aimed at reducing the impact of wildfires. The team behind the database enhancements, led by Boise State University doctoral student Yavar Pourmohamad and associate professor Mojtaba Sadegh, worked to incorporate a wide range of new attributes to provide a comprehensive and detailed view of wildfire trends and impacts.
The ability to infer valuable insights from the newly enhanced database is highlighted as a groundbreaking development in wildfire research. With the computational capacity and vast information contained in the database, researchers can ask critical questions that inform actions in different regions and help understand the factors associated with wildfire ignitions and their effects. The research team, including Oregon State University professor Erica Fleishman, notes that the database can play a significant role in advancing wildfire science and aiding in decision-making processes related to wildfire management.
A paper outlining the enhanced Fire Program Analysis Fire-Occurrence Database was recently published in the journal Earth System Science Data, showcasing the extensive work and collaboration involved in developing the updated database. Co-authors from various institutions, including Boise State University, University of California, Merced, USDA Forest Service, National Weather Service, University of Montana, and University of California, Irvine, contributed to the research efforts. The study was supported by the Joint Fire Science Program, a collaborative initiative of the U.S. Forest Service and U.S. Department of the Interior, further underscoring the importance and relevance of the database in advancing wildfire research and management.
Overall, the newly enhanced database is a significant advancement in wildfire prediction and management efforts, offering a wealth of data and insights that can be used to understand, prevent, and mitigate the impact of wildfires. By incorporating a wide range of environmental, social, and practical factors, the database provides a more holistic view of wildfire trends and impacts, allowing for evidence-based decision-making in wildfire management. The incorporation of artificial intelligence and machine learning models further enhances the database’s utility, enabling researchers to gain valuable insights into past and future wildfire occurrences. The collaborative effort behind the database enhancements illustrates the importance of data-driven approaches in tackling the challenges posed by wildfires and highlights the potential for cutting-edge research to inform effective wildfire management strategies.
