Population Dynamics in the Washington D.C. Metropolitan Area.

Authors: Tunaggina Khan*, GMU, Andreas Zufle, GMU, Dieter Pfoser, GMU, Olga Gkountouna , GMU
Topics: Urban and Regional Planning, Urban Geography, Population Geography
Keywords: Daytime Population Dynamics, Visualization, Commuter, Washington DC Metropolitan.
Session Type: Paper
Day: 4/3/2019
Start / End Time: 4:30 PM / 6:10 PM
Room: Council Room, Omni, West
Presentation File: No File Uploaded


How do we measure population? Is it nighttime, census-based population, or daytime, working population? According to the US Census Bureau, Washington D.C has the second highest estimated daytime population increase during normal business hours. Such a population swell poses serious challenges to city officials, but also provides opportunities to private businesses. As such, gauging the population dynamics of an urban area such as Washington, D.C. could be essential to a range of organizations and tasks. Focusing on commuter adjusted daytime population estimation in the city and surroundings, this work examines various modes of transportation in an effort to study their effect on population movement throughout the day. With different transportation means serving often complementary commuting needs, we incorporate a range of publicly available data (DC Metro trip data, Capital Bikeshare Data, Taxicab data) with demographic data (Census Bureau, American Community Survey) to investigate and visualize the daytime population dynamics. The base, or resident population of an area will be adjusted by considering commuters using the various transportation modes. We will employ exploratory data analysis to identify specific historic trends for each transportation mode. This will be complemented by an in-depth analysis of different transportation modes and their potentially similar or complementary passenger volumes over time. Data analysis results will be accompanied by visualizations of respective population mobility flows between areas. The overall goal for this work is to identify specific commuting patterns in the Washington DC metropolitan area.

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