Hazards SEES Type 2: WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

Hazards SEES 类型 2：WIFIRE：可扩展的数据驱动型野火监控、动态预测和弹性网络基础设施

• 批准号: 1331615
• 负责人: Ilkay Altintas
• 金额: $ 265.18万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1331615&HistoricalAwards=false
• 关键词: Hazards; SEES; Type; WIFIRE; Scalable

The University of California at San Diego (UCSD) is awarded a grant to build an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. San Diego Supercomputer Center (SDSC) and Calit2's Qualcomm Institute will build this integrated CI system for supporting social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change, together with collaborators from UCSD's Jacobs School of Engineering and UMD's Department of Fire Protection Engineering. The WIFIRE CI integrates networked observations, e.g., heterogeneous satellite data and real-time remote sensor data, with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters will architect and implement CI pathways that enable joint innovation for wildfire management. Scientific workflows will be used as an integrative distributed programming model and will simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before, during and after a wildfire. The approach is scalable which allows many sensors to be subjected to user-specified data processing algorithms to generate threshold alerts within seconds. Integration of this sensor data into both rapidly available fire image data and models will better enable situational awareness, responses and decision support at local, state, national, and international levels.The products of WIFIRE will be initially disseminated to project collaborators (SDG&E, CAL FIRE, USFS), covering academic, private, and government laboratories while generating value to emergency officials, and consequently to the general public. WIFIRE may be used by government agencies in the future to save lives and property during wildfire events, test the effectiveness of response and evacuation scenarios before they occur and assess the effectiveness of high-density sensor networks in improving fire and weather predictions. WIFIRE's high-density network, therefore, will serve as a testbed for future applications worldwide. The team is inclusive across a spectrum of collaborators and will create an open-source CI environment with intuitive workflows that lead to reusable software components for a wide range of science and engineering disciplines that can be extended to secondary education. Results are disseminated via an interactive website at SDSC in which students from high school to graduate level can participate in uploading their own data logging, data processing or data-driven alerts.

加利福尼亚大学圣地亚哥分校（UCSD）被授予一项赠款，以建立终端的网络基础设施（CI），称为WIFIRE，用于实时和数据驱动的模拟，对野火行为的预测和可视化。圣地亚哥超级计算机中心（SDSC）和Calit2的高通研究所将在面对城市动态和气候变化的情况下建立这种集成的CI系统，以支持对不断变化的火灾生态制度的社会生态弹性，以及UCSD的Jacobs Engineering of Engineering和UMD UMD Fire Fire Protection Engineering的合作者。 Wifire CI集成了网络观测值，例如，异质卫星数据和实时遥控传感器数据，以及信号处理，可视化，建模和数据同化的计算技术，以提供可扩展，技术和教育解决方案，以监视天气模式以预测野生火灾的广播速度。我们由科学家，工程师，技术人员，政府政策经理，私营企业和消防员组成的合作团队将建筑和实施CI途径，从而为野火管理提供联合创新。科学工作流将用作集成分布式编程模型，并将简化工程模块的实施，以进行数据驱动的模拟，预测和可视化，同时允许与大型计算设施进行集成。 Wifire将通过专门的Web接口和用户指定的警报对具有不同技能级别的用户进行扩展，以供野火之前，之中和之后广播给接收器的环境事件。该方法是可扩展的，可以使许多传感器受到用户指定的数据处理算法的影响，以在几秒钟内生成阈值警报。将这些传感器数据集成到快速可用的火灾图像数据和模型中，将更好地在本地，州，国家，国家和国际层面上提供情境意识，反应和决策支持。Wifire的产品最初将被散布到项目合作者（SDG＆E，CAL，CAL，USF，USF），涵盖学术，私人和政府实验室，同时为紧急官员以及一般公共官员以及一般的公共官员以及对公共官员的价值，并将其产生。政府机构将来可能会使用WIFIRE在野火事件期间挽救生命和财产，在发生之前测试响应和疏散场景的有效性，并评估高密度传感器网络在改善火灾和天气预测方面的有效性。因此，Wifire的高密度网络将作为全球未来应用的测试台。该团队在各种合作者中都具有包容性，并将创建一个具有直观工作流程的开源CI环境，从而为广泛的科学和工程学科提供可重复使用的软件组件，可以扩展到中等教育。结果通过SDSC的交互式网站传播，在该网站上，高中到研究生级别的学生可以参与上传自己的数据记录，数据处理或数据驱动的警报。