Abstract
Evacuations are a common practice to mitigate the potential risks and damages made by natural disasters. However, without proper coordination and management, evacuations can be inefficient and cause negative impact. Local governments and organizations need to have a better understanding of how the population responds to disasters and evacuation recommendations so as to enhance their disaster management processes. Previous studies mostly examine responses to evacuations at the individual or household level by using survey methods. However, population flows during disasters are not just the aggregation of individuals’ decisions, but a result of complex interactions with other individuals and the environment. We propose a method to model evacuation flows and reveal the patterns of evacuation flows at different spatial scales. Specifically, we gathered large-scale geotagged tweets during Hurricane Irma to conduct an empirical study. First, we present a method to characterize evacuation flows at different geographic scales: the state level, considering evacuation flows across southern states affected by Irma; the urban/rural area level, and the county level. Then we demonstrate results on the predictability of evacuation flows in the most affected state, Florida, by using the following environmental factors: the destructive force of the hurricane, the socioeconomic context, and the evacuation policy issued for counties. Feature analyses show that distance is a dominant predictive factor with counties that are geographically closer generally having larger evacuation flows. Socioeconomic levels are positively related to evacuation flows, with popular destinations associated to higher socioeconomic levels. The results presented in this paper can help decision makers to better understand population evacuation behaviors given certain environmental features, which in turn will aid in the design of efficient and informed preparedness and response strategies.
Highlights
Natural disasters are extreme events that can incur damage to the physical environment and infrastructures, which might, in turn, cause millions of losses and affect the routine life of residents [1]
Evacuation flows will be computed as flows from the pre-hurricane stay location to the landfall stay location; while re-entry flows will be computed as flows from stay locations during the landfall phase to stay locations during post-hurricane phase
8 Conclusions Understanding evacuation flows across different geographic areas can potentially enhance decision-making processes put in place by governments and organizations for disaster preparedness and response
Summary
Natural disasters are extreme events that can incur damage to the physical environment and infrastructures, which might, in turn, cause millions of losses and affect the routine life of residents [1]. Residents who are (2020) 9:29 potentially under the impact of disasters may choose to evacuate voluntarily or under the guidance of evacuation policies issued by local governments, so as to avoid life-threatening risk, reduce personal injuries and damages to property [3]. Due to the limited understanding of population evacuation behaviors, local governments may fail to provide proper guidance or management strategies, which can lead to inefficient evacuations or even cause negative consequences to surrounding areas. Local governments would benefit from a better understanding of how residents respond to evacuations so as to adjust the policies that aim to support vulnerable communities [6]. Traffic management benefit from an accurate foresight of the evacuation flows during disasters [8]
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