Authors: Yuqin Jiang*, University of South Carolina, Zhenlong Li, University of South Carolina
Topics: Cyberinfrastructure, Geographic Information Science and Systems, Transportation Geography
Keywords: Human mobility, disruptive events
Session Type: Paper
Start / End Time: 4:00 PM / 5:15 PM
Room: Tower Court C, Sheraton, IM Pei Tower, Second Floor Level
Presentation File: No File Uploaded
Measuring and understanding human mobility patterns has been a topic in scientific research for a long time. With interdisciplinary efforts, researchers have found that human mobility patterns show regularity and are highly predictable under normal routines. However, such regularity can be disrupted by different events, from local festivals to natural hazard evacuations. Due to various focuses of different studies, disruptions caused by events were analyzed case by case, especially for those who have large impact scales, such as hurricane or earthquake. However, limited attention was paid to disruptions caused by small scale events. In addition, most of those cases were studied individually, as a resulthow similar or different one event is from another is not comparable. To bridge the gap, this research develops a new measurement that aims to improve the current methodology to help better understand human mobility patterns during disruptive situations. Specially, this research implements the concept of entropy to measure the probability distribution of potential destination choices. Using New York City as a case study, this research shows the new measurement can not only identify disruptive events but also quantify the levels of disruption caused by different events. This method has practical applications in different areas including transportation analysis, event planning, and emergency management.