Vacated reverse engineers Google Street View to highlight the changing landscape of various neighborhoods throughout Manhattan and Brooklyn. The project finds cached, historic images of New York City hiding in plain sight on Google Street View. These images are algorithmically extracted by merging the Department of City Planning's PLUTO dataset with Google Street View, and searching for all properties that have been altered or constructed since Google Street View began (2007.)
Vacated mines and combines different datasets on vacant lots to present a sort of physical façade of gentrification, one that immediately prompts questions by virtue of its incompleteness: “Vacated by whom? Why? How long had they been there? And who’s replacing them?” Are all these changes instances of gentrification, or just some? While we usually think of gentrification in terms of what is new or has been displaced, Vacated highlights the momentary absence of such buildings, either because they’ve been demolished or have not yet been built. All images depicted in the project are both temporal and ephemeral, since they draw upon image caches that will eventually be replaced.
233 34th Street, New York, NY
Ultimately, “Vacated” is a walking tour of the changing urban landscape during the Bloomberg administration— it depicts some obvious examples of dramatic change, but in the end, it's up to the viewer to decide whether this change represents widespread gentrification.
(These images were specifically extracted from neighborhoods where housing costs have significantly increased since 2004.)
11 2nd Avenue, New York, NY
190 India Street, Brooklyn, NY
11 Bedford Ave., Brooklyn, NY
253 Eckford Street, Brooklyn, NY
91-93 Bowery Street, New York, NY
1 Clermont Street, Brooklyn, NY
Mapping Brooklyn, BRIC Arts Media House
Design & Violence, MoMA
Envision NY 2017, More Art
The Atlantic Cities
New York Magazine
The Washington Post
Q&A with More Art about Vacated commission.
This project began by examining whether temporal differences in Google Street View's cache could be used as a device to narrate rapidly changing urban landscapes. Since Google updates major roads on Street View more frequently, buildings located along intersections often contain images from two different time periods. This temporal gap can be large enough to span the entire construction of a new building.
To find these some of these gaps, I used the NYC Department of City Planning PLUTO dataset to extract addresses that had been built or altered since 2007. I then scraped Google Street View images for these locations to find cached, historical images.
During my research, I found that Google Street View cars often capture intersecting streets at different time periods. These time differences range from a few months to more than a year. If you visit these intersections in Google Street View and cross the intersection, the time period will change, revealing before and after imagery for the block. The PLUTO dataset contains a "Lot Type" field for each entry, which I used to find only properties that are located on intersections and were built or altered since 2007. Using this filtered dataset, I created a new script that scraped imagery for 2 different positions at each intersection, capturing before and after images for blocks en masse.
Original "Envision NYC 2017" commission
(includes building dates along blocks)
Stills, from the exhibition, of vacant lots since replaced with new housing developments.