Cross-comparative analysis of evacuation behavior after earthquakes using mobile phone data

Despite the importance of predicting evacuation mobility dynamics after large scale disasters for effective first response and disaster relief, our general understanding of evacuation behavior remains limited because of the lack of empirical evidence on the evacuation movement of individuals across multiple disaster instances. Here we investigate the GPS trajectories of a total of more than 1 million anonymized mobile phone users whose positions are tracked for a period of 2 months before and after four of the major earthquakes that occurred in Japan. Through a cross comparative analysis between the four disaster instances, we find that in contrast with the assumed complexity of evacuation decision making mechanisms in crisis situations, the individuals' evacuation probability is strongly dependent on the seismic intensity that they experience. In fact, we show that the evacuation probabilities in all earthquakes collapse into a similar pattern, with a critical threshold at around seismic intensity 5.5. This indicates that despite the diversity in the earthquakes profiles and urban characteristics, evacuation behavior is similarly dependent on seismic intensity. Moreover, we found that probability density functions of the distances that individuals evacuate are not dependent on seismic intensities that individuals experience. These insights from empirical analysis on evacuation from multiple earthquake instances using large scale mobility data contributes to a deeper understanding of how people react to earthquakes, and can potentially assist decision makers to simulate and predict the number of evacuees in urban areas with little computational time and cost, by using population density information and seismic intensity which can be observed instantaneously after the shock

Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.Comment: Submitted to IEEE Global Humanitarian Technologies Conference (GHTC) 201

Public Response to a Catastrophic Southern California Earthquake: A Sociological Perspective

This paper describes a hypothetical scenario of public response to a large regional earthquake on the southern section of the San Andreas Fault. Conclusive social and behavioral science research over decades has established that the behavior of individuals in disaster is, on the whole, controlled, rational, and adaptive, despite popular misperceptions that people who experience a disaster are dependent upon and problematic for organized response agencies. We applied this knowledge to portray the response of people impacted by the earthquake focusing on actions they will take during and immediately following the cessation of the shaking including: immediate response, search and rescue, gaining situational awareness through information seeking, making decisions about evacuation and interacting with organized responders. Our most general conclusion is that the actions of ordinary people in this earthquake scenario comprised the bulk of the initial response effort, particularly in those areas isolated for lengthy periods of time following the earthquake

Responding to natural disasters: Examining identity and prosociality in the context of a major earthquake

How does a major natural disaster relate to individuals’ orientation towards society? We collected repeated cross‐sectional surveys before (n = 644) and after the 2010 Chile earthquake (n = 1,389) to examine levels of national identity, prosocial values, helping motivations, and prosocial behaviours in the context of such a calamitous societal event. Our research questions, derived from the literature on helping in times of crisis, considered how natural disasters may implicate identity and prosociality, as well as how identity, prosocial values, and motivations are linked to prosocial action after a disaster. Higher levels of national identity, helping motivations, and disaster‐related helping were found after the earthquake, suggesting that in the aftermath of a disaster, people unite under a common national identity and are motivated to take action related to disaster relief. National identity and prosocial values were closely linked to helping after the earthquake, but specific helping motivations rarely predicted prosocial behaviours. Additionally, proximity to the epicentre was related to higher levels of national identity and participation in reconstruction efforts. These findings contribute to our understanding of people's responses to natural disasters and suggest ways of encouraging prosocial behaviour in the aftermath of unexpected tragic events

Crisis Communication Patterns in Social Media during Hurricane Sandy

Hurricane Sandy was one of the deadliest and costliest of hurricanes over the past few decades. Many states experienced significant power outage, however many people used social media to communicate while having limited or no access to traditional information sources. In this study, we explored the evolution of various communication patterns using machine learning techniques and determined user concerns that emerged over the course of Hurricane Sandy. The original data included ~52M tweets coming from ~13M users between October 14, 2012 and November 12, 2012. We run topic model on ~763K tweets from top 4,029 most frequent users who tweeted about Sandy at least 100 times. We identified 250 well-defined communication patterns based on perplexity. Conversations of most frequent and relevant users indicate the evolution of numerous storm-phase (warning, response, and recovery) specific topics. People were also concerned about storm location and time, media coverage, and activities of political leaders and celebrities. We also present each relevant keyword that contributed to one particular pattern of user concerns. Such keywords would be particularly meaningful in targeted information spreading and effective crisis communication in similar major disasters. Each of these words can also be helpful for efficient hash-tagging to reach target audience as needed via social media. The pattern recognition approach of this study can be used in identifying real time user needs in future crises