Authors: Yuqin Jiang*, University of South Carolina, Zhenlong Li, University of South Carolina
Topics: Cyberinfrastructure, Geographic Information Science and Systems, Hazards, Risks, and Disasters
Keywords: Mobility, evacuation, hurricane, Twitter
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Washington 6, Marriott, Exhibition Level
Presentation File: No File Uploaded
In recent years, coastal counties in the United States have suffered a lot from hurricanes. Evacuations have disrupted not only coastal counties, but also other inland places where evacuated people head to. Understanding people's evacuation patterns during hurricane is a critical call so that local officials can increase evacuation efficiency and effectiveness by providing better traffic control. In addition, inland places where coastal people head to can better prepare for hosting large amount of evacuated people. This research proposes a method to gain better understanding about people's evacuation destination based on an integration of mathematical probability model and individual's previous activity space retrieved from Twitter footprint. With more profound understanding of people's mobility patterns during evacuation, emergency management agents from local to federal levels can better plan for resource allocation during natural hazard response as well as simulate more sophisticated scenarios during preparedness phase.