Catching Patterns of Increased Difference: Gentrification and Degradation

Violet Whitney
Data Mining the City
3 min readApr 9, 2017
first image: gaudy gold signage advertises luxury (driving prices up) at locations next to Starbucks, second image: Family Dollar Locations attract competitors like the The 99 Cent Store driving prices downward

Object Recognition in Street Patterns

Pattern and object recognition in Google Street View images can be used to qualify and quantify the unique features that makeup various neighborhood ecosystems. The appearance of: power lines, subway bridges, brick walls, glass facades, or trees can indicate locations of investment and disinvestment and can help planners understand how features of an urban environment are interlinked.

Starbucks & Family Dollar

By sampling Street View Images from the geo-coordinates of Dollar Stores and Starbucks, these 2 sets of street images gave a clear image of how investment or lack of investment in the street fabric create cyclical environments of self-fulfilling prophecies. By narrowing down the sampling of images to these two datasets, object classification could be done manually. Future methods could use machine learning, to extend object classification well beyond human capacity and potentially learn like neighborhood characteristics of gentrification and degradation.

Starbucks and Family Dollar locations overlaid on map by median income show

Although it is reductive to draw a duality of high and low-income stores (neighborhood ecosystems are obviously more nuanced and complex), the intention is to be reductive enough to show ecosystems where opportunity for upward societal mobility exists and where it doesn’t.

left: glassy facades near Starbucks, right: closed brick facades near Family Dollar

While there is no inherent evil in a store trying to cater to their demographic, selecting sites in their target market, the outcome nonetheless defines a cyclical pattern of urban environments. As a Dollar Store moves in, so do the closed brick facades. When the city neglects neighborhoods without strong lobbies opting not to move power lines underground this in turn keeps sites affordable bringing in more dollar stores.

first image: patterns of trees sampled from Starbucks locations, second image: power lines thread through the sky near Family Dollar
first image: glassy Starbucks facades allow light to pour into the store, second image: Family Dollar often selects sites under bridges where darkness from the bridge makes sites less attractive yet more affordable

Interrupting the Cycle: Investing Without Gentrifying

This is not a claim for gentrification. Surely adding a Starbucks in a low-income neighborhood is not going to “save” it. Most likely the $5 coffees and higher rents would only push low-income residents out. However, stores should be cognizant of this effect when selecting sites. Furthermore, initiatives through government could support struggling store owners and invest in open store-fronts, street benches, trees, lowering power lines and other factors that make neighborhoods healthy welcoming environments. Other initiatives should encourage long-term affordability for residents to ensure a nicer environment does not simply gentrify.

Degradation Is Just Disinvesment

Keeping a neighborhood affordable should not require making the environment unpleasant. All people deserve to live in an environment that allows a healthy and happy life. Lack of resources can trap communities in poverty. Designers, policy makers, and entrepreneurs should recognize these implications in their work.

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Violet Whitney
Data Mining the City

Researching Spatial & Embodied Computing @Columbia University, U Penn and U Mich