Friday, November 24, 2017

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Evacuations from emergencies, like wildfires, depend on accurate population data. Evacuations from emergencies, like wildfires, depend on accurate population data.
 


Improving Wildfire Evacuation Planning

Researchers will coordinate with county emergency services, Red Cross and 2-1-1 San Diego to make evacuations more efficient.
By Michael Price
 

Disaster response officials painstakingly plan ahead for all scenarios, but no two emergencies are alike. A new National Science Foundation–funded partnership between San Diego State University, the County of San Diego Office of Emergency Services, the American Red Cross of San Diego/Imperial Counties and 2-1-1 San Diego aims to better prepare evacuation coordinators and resource managers for ever-changing emergency conditions. The grant from the National Science Foundation for nearly $450,000 will cover three years of study.

Evacuations typically occur in stages to avoid clogging roadways. To successfully execute such evacuations, decision makers depend on accurate population data. Most current evacuation models rely on housing population data from censuses, but populations are constantly shifting depending on the time of day, and many other factors, including the day of the week or special events that might be underway.

Combine data uncertainty with the inevitable chaos that occurs in a disaster and even the best evacuation plans can do awry, said geography professor Ming-Hsiang Tsou, director of SDSU’s Center for Human Dynamics in the Mobile Age, who is leading SDSU’s efforts in the partnership.

“One feature that many disasters have in common is their uncertain nature,” Tsou said. “Exact data are unlikely to be available, and there’s a high likelihood of social disruption.”

One way to quickly and accurately gauge an area’s real-time population is to look at social media usage, said Xianfeng Yang, an assistant professor of transportation engineering at SDSU.

“One of the most challenging things about evacuation planning is estimating dynamic population density,” Yang said. “We can use things like geotagged social media posts, remote sensing, geographic information system (GIS) data and crowd-sourcing to improve our estimations.”

SDSU researchers will look at ways to use data from social media, GIS and wildfire prediction software to design a web-based interactive evacuation planning tool that can help create efficient evacuation plans. For example, the standard evacuation plan may call for an area’s residents to use a local highway to evacuate. But during an emergency, social media data may indicate an abnormally high number of people in the area and a congested roadway. The new tool could send this real-time information back to the decision makers, who can change the evacuation plan in real time.

Atsushi Nara, a GIS expert and SDSU assistant geography professor, will work to develop the web-based decision support tool. His colleague, Ghanipoor Machiani, an assistant professor of transportation engineering at SDSU, will focus on the evacuation modeling and social perception monitor tools.

Red Cross officials said this kind of more precise evacuation planning tool could make a real difference for residents and disaster planners in times of crisis.

“Dr. Ming-Hsiang Tsou’s project to provide dynamic population and demographic data for evacuation planning has the potential to increase the Red Cross’s ability to provide a more effective response that could save lives,” said Brian Chambers, the Red Cross regional planning and recovery manager. “This is especially important in areas where wildfire is a threat and decisions need to be made quickly in a rapidly evolving and unpredictable situation.”