A national approach for integrating wildfire simulation modeling into Wild land Urban Interface risk assessments within the United States
A national approach for integrating wildfire simulation modeling into Wild land Urban Interface risk assessments within the United States
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DOI：
10.1016/j.landurbplan.2013.06.011
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发表时间：
2013-11-01
影响因子：
9.1
通讯作者：
Thompson, Matthew P.
中科院分区：
文献类型：
--
作者：
Haas, Jessica R.;Calkin, David E.;Thompson, Matthew P.
人类不断向火灾多发地区发展，加剧了人类生命面临的野火风险。因此，能够描述人口稠密地区的野火风险并识别风险相对较高的地理区域至关重要。野火风险分析的一个基本组成部分是确定野火发生的可能性以及与社会和生态价值的相互作用。存在多种火灾建模系统，可以提供野火可能性的空间解析估计，当与风险值地图相结合时，可以进行概率暴露分析。通过这项研究，我们证明了将燃烧概率与地理空间识别的人口稠密地区配对的可行性和实用性，以便为下一代基于风险的荒地-城市界面（WUI）地图的开发提供信息。具体来说，我们将新开发的住宅开发人口稠密地区数据集与随机的、空间明确的野火蔓延模拟模型相集成。我们将居住人口密度和燃烧概率分为三类（低、中、高），以创建风险矩阵并总结美国大陆各县级人口稠密地区的野火风险。我们的方法提供了一个新的框架，用于制作一致的国家地图，该地图可以在空间上识别人口稠密地区荒地火灾风险的程度和驱动因素。该框架推进了概率暴露分析，为应急管理、农村和城市社区规划工作以及更广泛的野火管理和政策制定提供决策支持。由 Elsevier B.V. 出版
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. Published by Elsevier B.V.