DOI: 10.1016/j.crm.2017.01.004
Scopus记录号: 2-s2.0-85011391963
论文题名: A novel method to identify likely causes of wildfire
作者: Mhawej M. ; Faour G. ; Adjizian-Gerard J.
刊名: Climate Risk Management
ISSN: 22120963
出版年: 2017
卷: 16 起始页码: 120
结束页码: 132
语种: 英语
英文关键词: Combination of factors
; Lebanon
; Likelihood
; Natural hazard
; Python
; Wildfire
英文摘要: Natural phenomena, such as wildfires, usually require the coincidence of several related factors in both time and space. In wildfire studies, literature-based factors were collected and listed in Mhawej et al. (2015). The question remains: which combination of factors leads to wildfires? In this context, a novel combination of wildfire likelihood factors was proposed in three different Lebanese forest covers (i.e., pine, oak, and mixed) and related literature-based factors to historical wildfire occurrences. The threshold values of each factor were deduced from the relationship between the element and number of fire occurrences. Each combination of factors was given a unique number. These mixtures corresponded to two, three, four or five factor groupings. The result was the association of each likelihood probability (i.e., low, medium, high, and very high) with different combinations of factors. Ultimately, using these combinations, the wildfire likelihood in Lebanese forests was efficiently and instantaneously generated. This approach could be portable to other Mediterranean regions and applied to several natural hazards. © 2017 The Authors Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/58970
Appears in Collections: 气候变化与战略
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作者单位: National Center for Remote Sensing, National Council for Scientific Research (CNRS), Riad al Soloh, Beirut, Lebanon; St Joseph University, Department of Geography, Damascus Street, Mar Mickael, Beirut, Lebanon
Recommended Citation:
Mhawej M.,Faour G.,Adjizian-Gerard J.. A novel method to identify likely causes of wildfire[J]. Climate Risk Management,2017-01-01,16