Visualizing Racial Segregation

In honor of this week’s Dr. Martin Luther King Day holiday, we encourage you to explore the continued pattern of racial segregation in housing with this map from the Weldon Cooper Center for Public Service at the University of Virginia. The map has one dot for every person in the United States as of the 2010 Census, with different colored dots for people reporting different races or ethnicities on the Census: red for Asian, orange for Hispanic, green for African American, blue for white, and brown for other. The image below shows St. Louis, Missouri, and its suburbs from this map.

Map of racial segregation in St. Louis, Missouri

 

Image Copyright, 2013, Weldon Cooper Center for Public Service, Rector and Visitors of the University of Virginia (Dustin A. Cable, creator)


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Teaching Basic Quantitative Concepts with Visualizations

Data do not speak. As has famously been noted, data and especially data displays –whether maps, statistics, or word clouds– can lie or at least be deceptive. Access to easy methods for generating visualizations and analyses may be as dangerous as liberating, unless we are careful as both producers and consumers.

The following three maps all show exactly the same data, but look very different—due to the choices made in display.

natbreaksdensitypopdenquart

The first map uses natural breaks in the data to separate categories. The second uses quartiles, a measure based on medians. For this the states are separated into 4 equal piles and the most densely-populated states are given the darkest color. Note how much variation this group exhibits. While the least dense two groups have only a small range, the range for the most densely populated is huge. Continue reading →

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Geovisualizing the Ebola Crisis

Media coverage of the Ebola virus outbreak has thus far represented a geospatial and cartographic moment.  Mapping of the outbreak and geovisualization of its different facets is doing much to frame public understanding of the crisis as well as the policies that are attempting to address it.

Population flow measured by mobile phones from Worldpop.org.uk/Flowminder

One the one hand, the widespread use of geovisualizations to report on the Ebola epidemic reflects the high density of information that maps provide.  This has only been increased by the swift integration of traditional cartography with animated graphics and other web-based media to create ever more visually appealing infographics that have a geographic twist.

Geovisualizations demonstrate the importance of place and scale—two fundamental aspects of geography—to the Ebola epidemic.  Maps of the worldwide locations of where infected patients are staying, the locations of medical centers equipped to handle Ebola are located, not to mention the geographic concentrations of new cases give readers a place-based sense of either unease or hope.  Maps of Ebola-related travel restrictions tell us how national governments are responding to the ongoing risk of spread.

But West Africa remains the epicenter of this Ebola outbreak and the region is already suffering a tremendous human and economic toll from the virus.  Using geospatial approaches to understand patterns of human mobility will is playing a central role in efforts to prevent the outbreak from reaching even greater proportions.  One of the best examples of this is work done by researchers associated with the Flowminder Foundation which reveals at an unprecedented level of detail the movements of people in and around the parts of West Africa with the highest concentrations of Ebola cases.  What made this work possible was the use of cell phone records, which are proprietary to the providing telecom companies and sensitive information for the phone users themselves.  Given the growing need for this type of spatial epidemiology to address fast breaking and complex emergencies like the Ebola outbreak, we can expect that norms around data availability and use to change quickly and in unexpected ways.


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