Research Triangle Park, NC (PRWEB) October 21, 2013
Synthetic populations viewer allows users to look at realistic, computer-generated households across the country by age, income, race and household size.
A new web-based mapping site allows users to see stark racial boundaries, subtle shifts in income, and intricate patterns of race, age, household size and income for any location in the United States.
The map, known as the synthetic population viewer and developed by researchers at RTI International, allows users to look at how the U.S. population organizes itself across the landscape and how age, income, race and household size vary within cities.
“This new era of complex, synthetic household data enables fine-scale, multidimensional demographic patterns and microcommunities to emerge from simple-to-use, web-based maps,” said Bill Wheaton, director of RTI’s Geospatial Science and Technology program.
The interactive map contains a representation of more than 112 million households and more than 280 million individuals in all 50 U.S. states and Washington, D.C. The information is based on the 2005–2009 American Community Survey.
Unlike typical census maps by county or census tract, these synthetic microdata are a representation of individual households.
“The data represent the reality of the U.S. household population very well. By representing each and every household as a point on the map, a wealth of complex patterns becomes apparent,” Wheaton said. “In order to protect privacy, the interactive map doesn’t show actual households in their exact locations like Google Earth. Nonetheless, the data represent real households in reasonably accurate detail, enabling the map to show complex population distributions.”
“It’s a rich tool for anyone interested in exploring the amazing diversity of human household populations in the U.S.,” Wheaton said.
Available online, the map and underlying data are free for use by everyone, from GIS professionals to college students working on projects to the general public simply interested in looking at population patterns.
“The underlying data can be used in computer simulations to track the spread of infectious disease or to understand how transportation networks are used, how people make choices about where to live, how a given intervention might affect obesity, how best to optimize supply chain operations, and many other uses,” Wheaton said. “But, aside from these complex research simulations, simply mapping the data as we’ve done with this viewer tells a story that everyone can understand.”
The project was funded as part of the Models of Infectious Disease Agent Study (MIDAS) grant from the National Institute of General Medical Sciences. MIDAS is a multimillion dollar bioterrorism defense initiative to help infectious disease researchers understand the dynamics of disease and test various mitigation options to reduce the effects of epidemics.