Graduation Year

2023

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

School of Geosciences

Major Professor

Steven Reader, Ph.D.

Committee Member

Christopher Emrich, Ph.D.

Committee Member

Fred Mannering, Ph.D.

Committee Member

Yi Qiang, Ph.D.

Committee Member

Graham Tobin, Ph.D.

Keywords

Decision Science, Disaster Informatics, Emergency Management, Geospatial Modeling, Predictors of Evacuation

Abstract

To reduce the devastating impacts of hurricanes on people’s lives, communities, and societal infrastructures, disaster management would benefit considerably from a detailed understanding of evacuation, including the socio-demographics of the populations that evacuate, or stay, down to disaggregated geographic levels such as neighborhoods. A detailed household evacuation prediction model for local neighborhoods requires both a robust household evacuation decision model and individual household data for small geographic units. To address the first of these, this dissertation performed a statistical meta-analysis of numerous survey-based hurricane evacuation studies to establish mean effect sizes for predictors impacting the household decision. To address the second, this dissertation performed an elegant population synthesis procedure for census block groups. The evacuation predication model built upon these two aspects is then used to predict how many, and what types of households, evacuate, or not, at the disaggregated geographic scale of census block groups.The results of the household evacuation prediction model indicate that the composite demographic profiles of the households, acting thru the household evacuation decision model, largely dictate patterns of evacuation. Some predictors which may have an outsize independent effect on the household evacuation decision model don’t always translate to those predictors which may exhibit the largest differentials in rates of evacuation/non-evacuation. This dissertation contributes significantly to the academic research literature on the evacuation behavior of people, the effect sizes of predictors and their heterogeneity, and the role of moderators such as model type (actual or hypothetical hurricanes), hurricane location, and model size. The dissertation is also a powerful example of applied research since it provides a framework, readily implemented in future software development, that can be actually used by disaster managers as they plan and implement strategies and practices to mitigate the worst immediate impacts of hurricanes, not only for the population that evacuates, but, more importantly perhaps, the population that remains.

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