All over the United States, data scientists, public planners, and retail organizations are working to understand the dynamics of segregation and social isolation in urban areas. Unfortunately, it can be tough to build a clear picture of these trends.
How can you tell which neighborhoods are segregated or socially isolated? How can you build an accurate and comprehensive picture of which neighborhoods get the most visitors, and where these visitors come from? And how can you identify areas of low social mobility?
In late 2019, researchers from the University of Wisconsin-Madison Geospatial Data Science Lab used SafeGraph’s free neighborhood insights data to study spatial interaction patterns between neighborhoods in Milwaukee. This study not only illustrated trends around racial segregation but also found several areas of high isolation and low social mobility.
As noted in the Wisconsin-Madison study, hidden biases of racial and socioeconomic preferences shape neighborhoods and urban areas throughout the United States, which can result in neighborhoods composed mostly of a particular race or income class, leading to a continued “segregation” of physical spaces.
Segregation has implications for all kinds of organizations. For state and municipal governments, segregation contributes to poor health and wellbeing outcomes and can also affect real estate values. For businesses, these trends can significantly affect opportunities for growth in particular areas and play a big part in site-selection.
On top of racial and economic divides, segregation also contributes to what academics refer to as “opportunity isolation.” As the Wisconsin-Madison study notes, “A growing body of scientific literature argues that disadvantaged neighborhoods of minority and/or poor residents face challenges to access what many experts refer to as social or opportunity isolation.”
“These opportunities include a lack of safe and healthy living environments, a lack of access to higher-paying jobs, and education.”
Being aware of segregation and opportunity isolation is one thing. But how can we measure these trends? How do we know which areas and communities are experiencing them the most?
According to the Wisconsin-Madison researchers, assessing the degree of social isolation at a large scale, outside of residential neighborhoods alone, is challenging. It requires further investigation to establish trends with any level of accuracy.
Fortunately, open data like SafeGraph’s can help to shed light on geospatial trends. Combined with census information, this data offers a new path to tell clear, crisp stories about highly nuanced social patterns.
Neighborhood isolation is prevalent in the metropolitan Milwaukee area, where systematic racism, for example, through exclusionary housing practices called “redlining,” has been prevalent for many years.
Drawing from SafeGraph’s Neighborhood Patterns data, researchers were able to tell a clear story about segregation and social isolation in Milwaukee. This analysis evaluated how race can be identified as either a limiting or empowering factor for Milwaukee neighborhood mobility.
To do this, these researchers analyzed origin and destination information for individuals travelling between two Census Block Groups (CBGs) in the Milwaukee metropolitan area during a one-month period in October 2018.
The researchers linked SafeGraph’s anonymized, aggregated foot-traffic data to demographic information provided by the American Community Survey to create an impactful visual representation of population movements across the city and its suburban neighborhoods.
The end result? Take a look at how this amazing diagram below represents the interconnectivity of seven discrete racial communities in the Milwaukee metropolitan area.
This representation of the way individuals travel between CBGs doesn’t just look cool: it also conveys important information about the effects of segregation and social isolation in the Milwaukee metropolitan area.
From this image, we can see clear patterns around the movement of different racial groups around different parts of the city, including the movements of predominantly white populations residing outside of Milwaukee County — more specifically, in Waukesha County.
This is a perfect example for showing how SafeGraph data can proactively identify trends and drive actionable solutions to addressing real and urgent social problems. In this case specifically, it has helped pinpoint otherwise “hidden” or unspoken trends that ultimately affect the wellbeing of different racial communities and social groups.
This then begs the question: which Milwaukee do you live in?
As the Wisconsin-Madison researchers’ report shows, there are clear divisions in the way these seven distinct communities move around the Milwaukee metropolitan area. These communities experience the city in different ways, each facing their own unique challenges as well as varying access to new opportunities.
This creates an entirely new understanding of segregation and social isolation, one that offers powerful insights for analysts, policy-makers, businesses, and virtually any other organizations that have interests in investing their time, energy, and business in Milwaukee.
The authors of the report point to a simple explanation of these trends: ‘White Flight’.
‘White Flight’ refers to a phenomenon by which white populations leave places, particularly urban environments, that have become increasingly populated by other racial groups over time.
Regrettably, ‘White Flight’ has contributed to lower levels of integration in the greater Milwaukee area for a long time now. In 2002, for example, fewer than one percent of residents in the metropolitan area outside the city lived on integrated blocks.
We can see this trend in community five as shown in the image above, where white residents account for 87.5% of the population. This represents the exodus of white people out of the city center and suggests a clearly defined environment of opportunity outside of inner Milwaukee.
In contrast, community seven, shown above in red, consists of predominantly African-American residents (84.2%) whose travels occur primarily within other African-American-dominated census block groups and rarely to environments of opportunity, including the downtown area.
“According to the recent American Community Survey, Milwaukee is the most segregated area in the United States.”
— ‘Understanding Neighborhood Isolation through Spatial Interaction Network Analysis Using Location Big Data’, in Journal of Environment and Planning (2019), Prestby, App, Kang, Gao
This contrast reflects the extent of existing segregation in Milwaukee. According to the recent American Community Survey, Milwaukee is the most segregated area in the United States.
So, how should we begin to address these problems? The first step, in our humble opinion, is to pinpoint and uncover new neighborhood insights through the use of open data.
Understanding complex trends and social patterns is challenging without access to the right data. This study shows how foot-traffic data can help quantify and visualize complex neighborhood trends, such as spatial isolation as it exists in relation to racial populations.
At SafeGraph, our goal is to democratize access to the best available data and help all kinds of businesses, organizations, governments, and researchers unlock new innovations and insights.
We offer the world’s most accurate dataset about physical places, making neighborhood consumer insights available for every Census Block Group, and equipping users to create powerful and compelling visualizations.
Our foot-traffic insights can:
We update our data monthly to reflect developments on the ground. We know physical places are always changing, and we keep a close eye on local developments via algorithmic techniques.
For anyone else interested in gleaning unique and powerful insights from over 6 million commercials places across the United States and Canada, you can now download up to $100 worth of SafeGraph data at no cost (no credit card required) when you use code MilwaukeeInsights at checkout on shop.safegraph.com.
That's it – that's all we do. We want to understand the physical world and power innovation through open access to geospatial data. We believe data should be an open platform, not a trade secret. Information should not be hoarded so that only a few can innovate.