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A spatio-temporal population model to support risk assessment and damage analysis for decision-making

机译:支持决策的风险评估和损失分析的时空人口模型

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The aim of this research is to develop and implement a simple spatio-temporal model of population location that might improve risk assessment and damage analysis for decision-making in both the Finnish Fire and Rescue Services and the Finnish Defence Forces. The motivation for the research is that present risk models do not take into account the temporal variation in population location during different times of the day. We use spatio-temporal modelling methods to model the population dynamics, and visualization techniques to represent the model outcomes. In addition, we apply the developed model to a damage-analysis application. The case study site is located in the centre of Helsinki. The model uses a basic population and workplace dataset maintained by the Helsinki Metropolitan Area Council. By means of this model, we intend to advance risk assessment, which considers the consequences of accidents. This model has the potential to help decision-makers evaluate their plans in several application areas—such as achieving better preparedness by having more reliable evacuation plans and resource allocation. In addition to the application-related technological research, a more generic framework about decision-making supported by spatio-temporal knowledge and visualization is presented.
机译:这项研究的目的是开发和实施一个简单的时空人口分布模型,以改善风险评估和破坏分析,以进行芬兰消防和救援部门以及芬兰国防军的决策。该研究的动机是,当前的风险模型没有考虑一天中不同时间的人口位置随时间的变化。我们使用时空建模方法来建模人口动态,并使用可视化技术来表示模型结果。此外,我们将开发的模型应用于损伤分析应用程序。案例研究站点位于赫尔辛基的中心。该模型使用由赫尔辛基都会区委员会维护的基本人口和工作场所数据集。通过这种模型,我们打算进行风险评估,该评估考虑了事故的后果。该模型有可能帮助决策者在多个应用领域中评估他们的计划,例如通过拥有更可靠的撤离计划和资源分配来实现更好的准备。除了与应用程序相关的技术研究之外,还提出了一个时空知识和可视化支持的更通用的决策框架。

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