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英文文献：Spatio-Temporal Modeling of Wildfire Risks in the U.S. Forest Sector-美国森林部门野火风险的时空模型
英文文献作者：Chen, Xuan,Goodwin, Barry K.
英文文献摘要：
In the US forestry industry, wildfire has always been one of the leading causes of damage. This topic is of growing interest as wildfire has caused huge losses for landowners, residents and governments in recent years. While individual wildfire behavior is well studied (e.g. Butry 2009; Holmes 2010), a lot of new literature on broadscale wildfire risks (e.g. by county) is emerging (e.g. Butry et al. 2001; Prestemon et al. 2002). The papers of the latter category have provided useful suggestions for government wildfire management and policies. Although wildfire insurance for real estate owners is popular, the possibility to develop a forestry production insurance scheme accounting for wildfire risks has not yet been investigated. The purpose of our paper is to comprehensively evaluate broadscale wildfire risks in a spatio-temporal autoregressive scenario and to design an actuarially fair wildfire insurance scheme in the U.S. forest sector. Our research builds upon an extensive literature that has investigated crop insurance modeling. Wildfire risks are closely linked to environmental conditions. Weather, forestland size, aspects of human activity have been proved to be crucial causal factors for wildfire (Prestemon et al. 2002; Prestemon and Butry 2005; Mercer et al. 2007). In light of these factors, we carefully study wildfires ignited by different sources, such as by arson and lightning, and identify their underlying causes. We find that the decomposition of forestland ecosystem and socio-economic conditions have significant impacts on wildfire, as well as weather. Our models provide a good fit to data on frequency and propensity for fires to exist (e.g. R-square ranges from 0.4 to 0.8) and therefore provide important fundamental information on risks for the development of insurance contracts. A number of databases relevant to this topic are used. With the Florida wildfire frequency and loss size database, a complete survey of four measurements of annual wildfire risks is implemented. These four measurements are annual wildfire frequency, burned area, fire per acre and burned ratio at county level. In addition, the national forestry inventory and analysis (FIA) database, Regional Economic Information Systems (REIS) database and the national weather database have supplied forestland ecosystem, socioeconomic, and weather condition information respectively. With our spatio-temporal lattice models, impacts of environmental factors on wildfire and implications of wildfire management policies are assessed. Forestland size, private owners’ share of forestland, population and drought would positively contribute to wildfire risks significantly. Cold weather and high employment are found to be helpful in lessening wildfire risks. Among the forestland ecosystem, oak / pine & oak / hickory forestland would reduce wildfire risks while longleaf / slash & loblolly / shortleaf pine forestland would have a mixed impact. An interesting finding is that oak / gum / cypress forestland would reduce wildfire frequency, but would enhance wildfire propensity at the same time. Hurricanes could intensify wildfire risks in the same year, but would significantly decrease the next year’s wildfire risks. Meanwhile, cross sample validation verifies that our method can forecast wildfire risks adequately well. Since our approach does not incorporate any fixed-effect indicator or trend as in the panel data analysis (Prestemon et al. 2002), it offers a universal tool to evaluate and predict wildfire risks. Hence, given environmental information of a location, a corresponding actuarially fair insurance rate can be calculated.
在美国林业中，野火一直是造成破坏的主要原因之一。近年来，野火给土地所有者、居民和政府造成了巨大损失，这一话题越来越受到人们的关注。而个体野火行为已得到充分研究(例如Butry 2009;Holmes 2010)，大量关于大规模野火风险(如按县分类)的新文献出现(如Butry et al. 2001;Prestemon等，2002)。后一类论文为政府的野火管理和政策提供了有益的建议。虽然对房地产所有者的野火保险很受欢迎，但对制定一项包含野火风险的林业生产保险方案的可能性尚未进行研究。本文的目的是在时空自回归的情形下，综合评估大规模野火风险，并设计一个精算公平的美国森林部门野火保险方案。我们的研究建立在广泛的研究作物保险模型的文献之上。火灾风险与环境条件密切相关。天气、林地面积、人类活动等方面已被证明是引发野火的重要原因(Prestemon等，2002年;Prestemon and Butry 2005;Mercer等，2007)。根据这些因素，我们仔细研究了由纵火、闪电等不同来源引起的火灾，并确定了其根本原因。研究发现，林地生态系统和社会经济条件的分解对森林火灾和气候都有重要影响。我们的模型很好地拟合了火灾发生频率和倾向的数据(例如，r平方在0.4到0.8之间)，因此为保险合同的发展提供了重要的基本风险信息。使用了许多与此主题相关的数据库。利用佛罗里达州野火频率和损失规模数据库，对每年野火风险的四种测量方法进行了完整的调查。这四个指标分别是年火灾频度、过火面积、每英亩过火面积和县级过火率。此外，国家林业调查与分析(FIA)数据库、区域经济信息系统(REIS)数据库和国家天气数据库分别提供了林地生态系统、社会经济和天气状况信息。利用该时空格构模型，对环境因素对森林火灾的影响和森林火灾管理政策的影响进行了评价。林地面积、私有面积、人口和干旱对森林火灾风险有显著的正向影响。寒冷的天气和高就业率有助于减少火灾风险。在林地生态系统中，橡树/松树和橡树/山核桃林地会降低野火风险，而长叶松/斜线松和火炬松/短叶松林地则会产生混合影响。一个有趣的发现是，橡树/树胶/柏树林地会降低野火发生的频率，但同时会增强野火发生的倾向。飓风会加剧当年的野火风险，但会显著降低明年的野火风险。同时，交叉样本验证验证了该方法能较好地预测火灾风险。由于我们的方法不像面板数据分析那样包含任何固定效应指标或趋势(Prestemon et al. 2002)，因此它提供了评估和预测野火风险的通用工具。因此，给定一个地点的环境信息，可以计算出相应的精算公平的保险费率。
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