A national approach for integrating wildfire simulation modeling into Wildland Urban Interface risk assessments within the United States

•Employs a probabilistic exposure analysis to identify the likelihood of populated places interacting with wildfire.•Classified at-risk areas according to a risk matrix comprised of population density and burn probability categories.•Risk matrix allows planners and managers a quick way to identify w...

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Bibliographic Details
Published in:Landscape and urban planning Vol. 119; pp. 44 - 53
Main Authors: Haas, Jessica R., Calkin, David E., Thompson, Matthew P.
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.11.2013
Elsevier
Subjects:
Animal, plant and microbial ecology
Applied ecology
Biological and medical sciences
Burn probability modeling
Computer simulation
Conservation, protection and management of environment and wildlife
data collection
Exposure
Exposure analysis
exposure assessment
Fires
Forest and land fires
Fundamental and applied biological sciences. Psychology
General aspects
General aspects. Techniques
Human
human development
humans
Methods and techniques (sampling, tagging, trapping, modelling...)
Phytopathology. Animal pests. Plant and forest protection
planning
population density
Probabilistic methods
Probability theory
Residentially developed populated areas
Risk
simulation models
United States
Weather damages. Fires
Wildfire risk assessment
Wildfires
wildland fire management
Wildland urban interface
United States
North America
America
USA
Exposure analysis
Wildland urban interface
Wildfire risk assessment
Burn probability modeling
Residentially developed populated areas
Vegetation fire
Urban area
Risk analysis
Environmental management
Modeling
ISSN:0169-2046, 1872-6062
Online Access:Get full text
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Summary:•Employs a probabilistic exposure analysis to identify the likelihood of populated places interacting with wildfire.•Classified at-risk areas according to a risk matrix comprised of population density and burn probability categories.•Risk matrix allows planners and managers a quick way to identify where the risk is located spatial, and to qualify the driving factors of the risk (population or burn probability or both).•Suggests a number of ways that managers and planners can use this information for decision-making, fuels modifications and residential planning. Ongoing human development into fire-prone areas contributes to increasing wildfire risk to human life. It is critically important, therefore, to have the ability to characterize wildfire risk to populated places, and to identify geographic areas with relatively high risk. A fundamental component of wildfire risk analysis is establishing the likelihood of wildfire occurrence and interaction with social and ecological values. A variety of fire modeling systems exist that can provide spatially resolved estimates of wildfire likelihood, which when coupled with maps of values-at-risk enable probabilistic exposure analysis. With this study we demonstrate the feasibility and utility of pairing burn probabilities with geospatially identified populated places in order to inform the development of next-generation, risk-based Wildland-Urban Interface (WUI) maps. Specifically, we integrate a newly developed Residentially Developed Populated Areas dataset with a stochastic, spatially-explicit wildfire spread simulation model. We classify residential population densities and burn probabilities into three categories (low, medium, high) to create a risk matrix and summarize wildfire risk to populated places at the county-level throughout the continental United States. Our methods provide a new framework for producing consistent national maps which spatially identifies the magnitude and the driving factors behind the wildland fire risk to populated places. This framework advances probabilistic exposure analysis.for decision support in emergency management, rural and urban community planning efforts, and more broadly wildfire management and policy-making.
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ISSN:0169-2046
1872-6062
DOI:10.1016/j.landurbplan.2013.06.011