Background: Live fuel moisture content (LFMC) is a key environmental indicator used to monitor for high wildfire risk conditions. Many statistical models have been proposed to predict LFMC from remotely sensed data; however, almost all these estimate current LFMC (nowcasting models).
Wildfires pose a large and growing threat to communities across California, and understanding fire vulnerability and impacts can enable more effective risk management. Government hazard maps are often used to identify at-risk areas, but hazard zones and fire experience may have different implications for communities.
Recent increases in Douglas-fir (Psuedotsuga menziesii var. menziesii) mortality in the Klamath Mountains ecoregion raise concerns about the long-term resilience of Douglas-fir in the ecoregion and increased potential for uncharacteristic wildfire.
Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown.
Highlights • People with egalitarian cultural traits are more likely to engage in fire mitigation behaviors. • Concern, experience, and proximity all have a positive relationship to engagement in fire mitigation behaviors. • Fire-resistant building materials and landscaping requirements are effective policy tools for homeowner mitigation actions.
Despite recent research, a systematic approach to understanding wildfire governance is lacking. This article addresses this deficit by systematically reviewing governance theories and concepts applied so far in the academic literature on wildfires as a step toward achieving their more effective and holistic management.
(1) Background: Federal land managers in the US are charged with risk-based decisionmaking which requires them to know the risk and to direct resources accordingly. Without understanding the specific factors that produce risk, it is difficult to identify strategies to reduce it. (2) Methods: Risk characterized by U.S.
Fire location and burning area are essential parameters for estimating fire emissions. However, ground-based fire data (such as fire perimeters from incident reports) are often not available with the timeliness required for real-time forecasting.
Wildfire is a complex problem because of the diverse mix of actors and landowners involved, uncertainty about outcomes and future conditions, and unavoidable trade-offs that require ongoing negotiation. In this perspective, we argue that addressing the complex challenge of wildfire requires governance approaches designed to fit the nature of the wildfire problem.
The methodology used by the First Street Foundation Wildfire Model (FSF-WFM) to compute estimates of the 30-year, climate-adjusted aggregate wildfire hazard for the contiguous United States at 30 m horizontal resolution is presented.