We use cookies to understand how the website is being used and to ensure you get the best possible experience.
By continuing to use this site, you consent to this policy. About cookies

Analyzing Urban Walkability with Social Explorer

THURSDAY, OCT 17, 2019

“I use Social Explorer basically everyday for all sorts of things. From looking up facts, downloading data, and visualizing key data points to thinking about what interesting things I can find that sheds new light on different types of socioeconomic phenomena. Social Explorer helps me crystallize my thoughts and shapes how I think or talk about my ideas.”

– Devin Michelle Bunten, Assistant Professor of Urban Economics and Housing, MIT


Dr. Devin Michelle Bunten, Assistant Professor at the Department of Urban Studies and Planning at MIT, researches urban economics, housing policy, and urban economic history. A writer and economist, Dr. Bunten uses Social Explorer’s rich data resources and user-friendly mapping tools to examine socioeconomic phenomena such as neighborhood change, effects of gentrification and white flight, and urban walkability.

For Dr. Bunten, Social Explorer is a “convenient hub” for downloading a large variety of datasets, a teaching tool for helping her students develop data skills, and most importantly, a critical component of her research process. She uses Social Explorer to help shape her ideas, crystallize her thoughts, and share her insights with her students and on social media. 


Walkability is the quantitative method of studying how friendly an urban environment is to the activity of walking. While researching the effects of transport networks on cities, Dr. Bunten became interested in exploring the issue of urban walkability in greater detail.

Dr. Bunten required census block level data for analyzing minute variations in walkability among cities of different sizes. Census blocks are the smallest geographic unit for which the Census Bureau collects data. Blocks represent streets, roads, and railroads, bodies of water, and other visible physical and cultural features. In cities, a census block roughly corresponds to a city block.

Census tracts typically range between 1,000 and 8,000 inhabitants, while a census block group may consist of 600 to 3,000 inhabitants. In comparison to these two levels, block level data can capture much higher variation in terms of minute details. The story told at the block level as opposed to the tract level can be very different. Hence, finding the right tool that would allow her to easily explore and visualize this kind of highly granular data was vital to Dr. Bunten’s research.


Using Social Explorer’s powerful and intuitive mapping tools, Dr. Bunten was easily able to explore and visualize block level data for her walkability analysis. As Dr. Bunten pointed out, “I don’t have another tool which helps me see these differences.” Insights gained from visualizing data at such a granular level could help Dr. Bunten understand how different cities function, their unique barriers to walkability, and trade-offs between different transportation modes in a particular city and so on.

Mapping block level data

Dr. Bunten’s empirical inquiry into urban walkability began taking shape after Social Explorer added block level data from the 2010 Census. Being able to visualize this high level of granularity in the data on Social Explorer proved crucial toward facilitating her research.

This side-by-side map illustrates Philadelphia’s population density (Census 2010) at the census block and census tract levels respectively. Click here to explore further.

Taking the city of Philadelphia as an example, the block level data can end up making the population density map look very different. Notice how City Hall is its own census block in Map 1. However, when lumped together with other blocks in a census tract, this entire stretch appears to be as densely populated as a suburban area. With Social Explorer’s powerful mapping tools, Dr. Bunten was easily able to parse these differences in detail. 

Weighing every detail

For Dr. Bunten, being able to visualize population density, a determining factor for walkability, at the census block level on Social Explorer offered her valuable insights. Visualizing data at the census block level as opposed to the tract level not only brings out minute variations in the population density data, but also illustrates barriers to walkability. 

Freeways, for instance, are typically wide enough to get their own census blocks. Hence, when a freeway cuts through a city, it looks like a snake of empty area. Although it is a road one can drive on, it ends up functioning more as a barrier to walkability. It is also one of the many details that pop up clearly in the block level data map on Social Explorer. 

In this Social Explorer map of Philadelphia, there are huge white areas empty of population to the north of Center City. These spaces are marked by freeways, expressways, urban renewal areas, correctional facilities, etc. all of which Dr. Bunten considers to be barriers to walkability. Click here to explore further.

Sharing your insights

Dr. Bunten also examined the distribution of different racial groups in her walkability analysis. Neighborhoods in West Philadelphia near the university areas which appeared to be seemingly integrated at the census tract level, block level data for race on Social Explorer clearly showed a lack of racial integration.

Furthermore, even though these contiguous places show up as relatively dense, Dr. Bunten reasoned that this density probably resulted from crowding in these low income areas rather than being an indicator of great walkability.

These Social Explorer side-by-side maps illustrate racial composition at census tract and census block levels (Census 2010) for Philadelphia respectively. Click here to explore further.

Dr. Bunten often shares “little stories” about her Social Explorer findings in the form of interactive maps on social media. “Urban theory is all about telling stories to make sense of things,” said Dr. Bunten. “I have been enjoying the block stuff on Social Explorer so much because it tells a clear story.”

Author: Amrapali Saha

Data insights are waiting to be uncovered
Get started

Already using Social Explorer? Log in.