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Modelling Individual Evacuation Decisions during Natural Disasters: A Case Study of Volcanic Crisis in Merapi, Indonesia

机译:模拟自然灾害期间的个人疏散决策:以印度尼西亚默拉比火山危机为例

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As the size of human populations increases, so does the severity of the impacts of natural disasters. This is partly because more people are now occupying areas which are susceptible to hazardous natural events, hence, evacuation is needed when such events occur. Evacuation can be the most important action to minimise the impact of any disaster, but in many cases there are always people who are reluctant to leave. This paper describes an agent-based model (ABM) of evacuation decisions, focusing on the emergence of reluctant people in times of crisis and using Merapi, Indonesia as a case study. The individual evacuation decision model is influenced by several factors formulated from a literature review and survey. We categorised the factors influencing evacuation decisions into two opposing forces, namely, the driving factors to leave (evacuate) versus those to stay, to formulate the model. The evacuation decision (to stay/leave) of an agent is based on an evaluation of the strength of these driving factors using threshold-based rules. This ABM was utilised with a synthetic population from census microdata, in which everyone is characterised by the decision rule. Three scenarios with varying parameters are examined to calibrate the model. Validations were conducted using a retrodictive approach by performing spatial and temporal comparisons between the outputs of simulation and the real data. We present the results of the simulations and discuss the outcomes to conclude with the most plausible scenario.
机译:随着人口数量的增加,自然灾害影响的严重性也在增加。部分原因是因为现在有更多的人居住在容易受到危险自然事件影响的区域,因此,当此类事件发生时需要撤离。疏散可能是使任何灾难的影响最小化的最重要措施,但在许多情况下,总有人不愿离开。本文介绍了一种基于主体的疏散决策模型(ABM),重点是在危机时期不愿出现的人的涌现,并以印度尼西亚梅拉比(Merapi)为例进行研究。个人避难决策模型受文献回顾和调查中阐述的几个因素影响。我们将影响疏散决策的因素分为两个相反的因素,即离开(撤离)和留下的驱动因素,以建立模型。代理人的疏散决定(停留/离开)是基于使用基于阈值的规则对这些驱动因素的强度进行的评估。该ABM与来自人口普查微数据的合成种群一起使用,决策规则以每个人的特征为特征。研究了具有不同参数的三种情况以校准模型。通过执行模拟输出与实际数据之间的时空比较,使用追溯方法进行了验证。我们介绍了模拟的结果,并讨论了结果以得出最合理的结论。

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