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Visualizing Human Migration through Space and Time

Oral presentation on the 1st International Symposium on Spatiotemporal Computing, Fairfax, Virginia., July 13-15, 2015.


Human migration has been an important activity in human societies ever since Homo sapiens walked on earth. As globalization intensifies in the modern era, human migration has become even more important, impacting almost all aspects of human lives and the environment. Understanding this phenomenon, its causes, processes and impacts often starts from visualizing and investigating its spatiotemporal patterns. This study takes on the task of building a generic online platform for quickly ingesting human migration data in plain text or tabular format, matching the records with pre-established geographic features such as administrative polygons, symbolizing the migration flow by circular arcs of varying color and weight based on the flow attributes, connecting the centroids of the origin and destination polygons, and allowing the user to select either an origin or a destination feature to display all flows in or out of that feature through time. The methodology was first developed using ArcGIS Server for a world-wide cross-country migration, and later applied to visualizing domestic migrations within China between provinces, and with the USA between states, all through multiple years. Technical challenges of this study include (1) Simplifying the shapes of features to enhance user interaction, rendering performance and accommodate application scalability; (2) Enabling the temporal renderers to provide time-based rendering of features and the flow among them; and (3) Developing a responsive web design (RWD) application to provide an optimal viewing experience. The platform is available online for the public to use, and the methodology is proven to be easily adoptable to visualizing any flow (not only human but also goods, capital, etc.) between multiple origins and destinations across space and time.

Publication Date  July, 2015
Author(s)  Giovanni Zambotti, Weihe Wendy Guan, Justin Gest
Publication type  Presentations