Social media platforms such as Twitter with user-generated contents provide great
potentials to better understand the spatiotemporal and transportation pattern of
evacuation behaviors during hurricanes. Hurricane Harvey was the costliest tropical
cyclone on record (tied with Hurricane Katrina of 2005), inflicting roughly $125
billion in damage across the Houston metropolitan area and Southeast Texas. It
lasted from about mid-Aug until early Sep 2017, with many records for rainfall and
landfall intensity set during that time.
The overall map visualizes the trajectories generated based on a Twitter dataset
relevant to 2017 Hurricane Harvey. The transportation mode (flight vs. drive) is
calculated using machine learning algorithms considering multiple spatiotemporal and
semantic factors, based on manually classified ground truth dataset. Technical
details of the transportation mode detection process are introduced in the
corresponding research paper. The four stage-specific maps display the aggregated
trajectories at CBSA (core-based statistical area) level during the 4 stages of
Hurricane Harvey correspondingly, indicating the connections among major
metropolitan areas. Both the line width and opacity represent the volume of
connections between two cities. Only strong connections are displayed, while the
weaker ones are hidden.
This map is selected to be published on
Esri Map Book Volume 39
(2024). The initial version is presented at North American Cartographic Information
Society (NACIS)
2021 Student Map Gallery
. The updated version is displayed at
Map Gallery
of Big Ten Academic Alliance (BTAA) Geospatial Information Network (GIN) 2023
Conference.
Below are examples of original maps in research paper which this comprehensive map
is based on.