Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science
Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science
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DOI：
10.1007/s11069-016-2678-1
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发表时间：
2017-03
期刊：
影响因子：
3.7
通讯作者：
Amirhassan Kermanshah;S. Derrible
中科院分区：
文献类型：
--
作者：
Amirhassan Kermanshah;S. Derrible
本文的主要目的是研究道路网络对极端洪水事件的鲁棒性，这些事件可能以相对不可预测的方式对整个区域系统产生负面影响。在这里，我们采用了一种确定性的方法来模拟极端洪水事件在两个城市，纽约市和芝加哥，删除整个路段的道路系统使用美国联邦应急管理局洪泛区。然后，我们衡量的变化，真实的行程，可以完成（使用出行需求数据），地理信息系统的属性，网络拓扑指标。我们特别测量和讨论了洪水后介数中心性是如何重新分配的。一般来说，道路网络等空间系统的鲁棒性取决于许多因素，包括系统大小（节点和链路的数量）和网络的拓扑结构。可以预期的是，鲁棒性还取决于地理位置，自然风险更高的城市往往不那么鲁棒，因此鲁棒性的概念很快就会对个体环境敏感。
The main objective of this article is to study the robustness of road networks to extreme flooding events that can negatively affect entire regional systems in a relatively unpredictable way. Here, we adopt a deterministic approach to simulate extreme flooding events in two cities, New York City and Chicago, by removing entire sections of road systems using U.S. FEMA floodplains. We then measure changes in the number of real trips that can be completed (using travel demand data), Geographical Information Systems properties, and network topological indicators. We notably measure and discuss how betweenness centrality is being redistributed after flooding. Broadly, robustness in spatial systems like road networks is dependent on many factors, including system size (number of nodes and links) and topological structure of the network. Expectedly, robustness also depends on geography, and cities that are naturally more at risk will tend to be less robust, and therefore the notion of robustness rapidly becomes sensitive to individual contexts.