A framework for evacuation hotspot detection after large scale disasters using location data from smartphones: case study of Kumamoto earthquake
A framework for evacuation hotspot detection after large scale disasters using location data from smartphones: case study of Kumamoto earthquake
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DOI：
10.1145/2996913.2997014
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发表时间：
2016-10
期刊：
影响因子：
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通讯作者：
T. Yabe;K. Tsubouchi;Akihito Sudo;Y. Sekimoto
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文献类型：
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作者：
T. Yabe;K. Tsubouchi;Akihito Sudo;Y. Sekimoto
大规模的灾害造成严重的社会混乱，引发大规模的疏散活动。有效管理疏散避难所对灾害管理至关重要。2016年4月16日，日本熊本县发生7.3级大地震。结果，1万多座建筑物严重受损，10万多人不得不撤离家园。地震发生后，决策者花了好几天时间才掌握人们撤离的地点，这延误了物资的分配和救援。由于一些人被疏散到没有被指定为疏散避难所的地方，情况变得更加复杂。掌握疏散热点的传统方法需要步行实地调查，这需要花费时间，而且很难在混乱的危险发生后立即执行。我们提出了一个新的框架，利用智能手机收集的位置数据有效地估计大型灾害后的疏散热点。为了验证我们的框架并使用我们的输出显示有用的分析，我们使用雅虎日本收集的智能手机的GPS数据演示了熊本地震的框架。我们通过检查所设设施，并将人口转移结果与报纸报道进行比较，验证了我们对疏散热点的估计精度很高。此外，我们还使用我们的框架输出展示了有助于决策者的分析，例如每个热点的人口转变和功能期。通过检查处理时间也验证了我们的框架的效率，表明它可以有效地利用在任何规模的灾难。我们的框架为在各种大规模灾害后管理疏散避难所的决策者提供了有用的输出。
Large scale disasters cause severe social disorder and trigger mass evacuation activities. Managing the evacuation shelters efficiently is crucial for disaster management. Kumamoto prefecture, Japan, was hit by an enormous (Magnitude 7.3) earthquake on 16th of April, 2016. As a result, more than 10,000 buildings were severely damaged and over 100,000 people had to evacuate from their homes. After the earthquake, it took the decision makers several days to grasp the locations where people were evacuating, which delayed of distribution of supply and rescue. This situation was made even more complex since some people evacuated to places that were not designated as evacuation shelters. Conventional methods for grasping evacuation hotspots require on-foot field surveys that take time and are difficult to execute right after the hazard in the confusion. We propose a novel framework to efficiently estimate the evacuation hotspots after large disasters using location data collected from smartphones. To validate our framework and show the useful analysis using our output, we demonstrated the framework on the Kumamoto earthquake using GPS data of smartphones collected by Yahoo Japan. We verified that our estimation accuracy of evacuation hotspots were very high by checking the located facilities and also by comparing the population transition results with newspaper reports. Additionally, we demonstrated analysis using our framework outputs that would help decision makers, such as the population transition and function period of each hotspot. The efficiency of our framework is also validated by checking the processing time, showing that it could be utilized efficiently in disasters of any scale. Our framework provides useful output for decision makers that manage evacuation shelters after various kinds of large scale disasters.