  Understanding individuals' behavior during hurricane evacuation is of
paramount importance for local, state, and government agencies hoping to be
prepared for natural disasters. Complexities involved with human
decision-making procedures and lack of data for such disasters are the main
reasons that make hurricane evacuation studies challenging. In this paper, we
utilized a large mobile phone Location-Based Services (LBS) data to construct
the evacuation pattern during the landfall of Hurricane Irma. By employing our
proposed framework on more than 11 billion mobile phone location sightings, we
were able to capture the evacuation decision of 807,623 smartphone users who
were living within the state of Florida. We studied users' evacuation
decisions, departure and reentry date distribution, and destination choice. In
addition to these decisions, we empirically examined the influence of
evacuation order and low-lying residential areas on individuals' evacuation
decisions. Our analysis revealed that 57.92% of people living in mandatory
evacuation zones evacuated their residences while this ratio was 32.98% and
33.68% for people living in areas with no evacuation order and voluntary
evacuation order, respectively. Moreover, our analysis revealed the importance
of the individuals' mobility behavior in modeling the evacuation decision
choice. Historical mobility behavior information such as number of trips taken
by each individual and the spatial area covered by individuals' location
trajectory estimated significant in our choice model and improve the overall
accuracy of the model significantly.
