While wildland firefighters may work in emergency manage- ment periodically and some commonalities with struc- tural firefighting do exist, many of the occupational and environmental exposures and hazards that wildland fire- fighters face are distinctly different from other classes of emergency responders ...
Together, they form what is called the ”fire triangle”. The first element is the heat, which is the spark or the source that brings fuel to its ignition temperature. It's source can be human, such as a lit match, or natural, such as lightning strikes. The second element is the ...
The results show that the neighborhoods in Bariloche can be divided into three classes: High Socioeconomic Fire Risk neighborhoods, including neighborhoods with the highest fire rates, where people have low instruction level, high levels of unsatisfied basic needs and high unemployment levels; Low ...
Int. J. Wildland Fire 27, 1–14 (2017). Article Google Scholar Koksal, K., McLennan, J., Every, D. & Bearman, C. Australian wildland–urban interface householders’ wildfire safety preparations: ‘Everyday life’ project priorities and perceptions of wildfire risk. Int. J. Disaster ...
The National Interagency Fire Center (NIFC) posts annual fire season information in its Esri Community group and makes that required reading for all members. What the NIFC team wanted was a platform where important communication could be shared with the whole ArcGIS Online organization at once and...
eventually used these three feature-classes in the wildland fire-induced risk zonation and discussed further in the following sub-section. 3.3. Delineating WUI, Risk Zonation and Assessment In order to delineate risk zones, and assess the presence/absence of vegetation (i.e., fuels) within these...
Fire locations (between 2000 and 2021). 2.2.2. Machine Learning Methods In cases where there is an imbalance between classes in a dataset, machine learning algorithms usually make biased decisions in favor of the majority class. Since there was an imbalance between classes in the dataset used...
EditionBuilding Fire Prediction and SuppressionBushfire in TasmaniaClimate and Human-Driven Impacts on Tropical RainforestsCoal Fires and Their Impact on the EnvironmentCombustion Process, Emission Control, and Energy Generation in Internal Combustion EnginesComputer Vision and Artificial Intelligence in Fire ...
The wildland-urban interface (WUI)—the area where wildland vegetation and urban buildings intermix—is at a greater risk of fire occurrence because of extensive human activity in that area. Although satellite remote sensing has become a major tool for assessing fire damage in wildlands, it is un...
We eventually used these three feature-classes in the wildland fire-induced risk zonation and discussed further in the following sub-section. 3.3. Delineating WUI, Risk Zonation and Assessment In order to delineate risk zones, and assess the presence/absence of vegetation (i.e., fuels) within ...