系统仿真学报 ›› 2016, Vol. 28 ›› Issue (10): 2567-2573.

• 仿真系统与技术 • 上一篇    下一篇

海啸可视化仿真及灾害风险评估

解翠, 寻锦锦, 周小伟, 董军宇   

  1. 中国海洋大学计算机科学与技术系,山东 青岛 266100
  • 收稿日期:2015-05-31 修回日期:2016-07-14 出版日期:2016-10-08 发布日期:2020-08-13
  • 作者简介:解翠(1977-),女,山东青岛,博士,讲师,研究方向为可视化、分布交互仿真和虚拟现实;寻锦锦(1990-),女,山东济宁,硕士,研究方向为可视化仿真。
  • 基金资助:
    国家自然科学基金(61271405, 41576011, 61401413); 中国海洋大学青年基金(201213016)

Visual Tsunami Simulation and Disaster Risk Assessment

Xie Cui, Xun Jinjin, Zhou Xiaowei, Dong Junyu   

  1. Computer Science and Technology Department of Ocean University of China, Qingdao 266100, China
  • Received:2015-05-31 Revised:2016-07-14 Online:2016-10-08 Published:2020-08-13

摘要: 通过对中国南海潜在海啸事件进行有效地建模和可视化仿真,模拟多种海啸发生、传播、淹没过程,并统计海啸淹没的概率、程度和范围等信息。利用GIS分析和图像处理技术对研究区域的建筑物/重要设施的位置和功能类型等信息进行提取和分类,再进行有效的人口分布建模和人员响应能力的易损性估计,结合地理环境信息和历史灾害记录,采用改进的风险评估方法,不仅考虑遭受海啸袭击概率,还考虑了淹没速度、深度及人口密度和疏散时间等因素,基于决策树分类判别方法生成海啸风险图,帮助找出易受灾的危险区进行早期预警,辅助灾害管理和防灾减灾预案的制定。

关键词: 海啸, 可视化仿真, 风险评估, 人口分布建模

Abstract: Based on the effectively modeling and visual simulation of the potential tsunami event in the South China Sea, the tsunami generation, propagation, runup and inundation could be visually simulated with multiple scenarios. The inundation probability, the flood inundation area and degree were computed. The location and function of buildings/critical facilities in the study area were extracted and classified by GIS analysis and image processing technology. Then the population distribution was effectively modeled and the vulnerability of people response was estimated for risk assessment combining with the geographical information and the historical disasters record. This improved method considered the inundation probability of tsunami, the flood speed, depth, and other factors such as population density and available evacuation time, etc. The tsunami risk map was generated based on the decision tree classification method, which helps find the high risk areas for early warning and assists in disaster management and disaster prevention and mitigation.

Key words: tsunami, visual simulation, risk assessment, population distribution modeling

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