The Value of Street-Level Greenness

Urban, street-level greenery is empirically documented to improve mental and physical health, increase productivity and urban environmental equality, and reduce carbon footprints. In addition, these benefits raise residents' welfare, which has been correlated with increases in residential house prices. The first of its kind to study street-level greenery from a commercial real estate standpoint, this research measures street-level greenness in New York City through a novel Green View Index (GVI), using Google Street View images and assessing the impacts of greenness on commercial real estate prices. Using a sample of office transactions, we spatially correlate Google Street View Images for New York City over the 2010 to 2017 period. We find an 8.9% to 10.5% statistically, economically and positive transaction premium, and a 5.6% to 7.8% rent premium for offices with low to high street-level greenness relative to those building transactions spatially correlated with very low greenness. Estimations are robust to proximity to parks, subway stations, sidewalk widths, household income levels and investments by Building Improvement Districts, as well as other vital and standard office valuation features. By documenting the role of greenery in commercial building valuations, our results give a more complete understanding of the value of greenness in urban environments, and the economic role that urban landscape architecture, planning and development has upon cities.


At each assigned coordinate, we calculated the average percentage of green pixels from collected Google Street View images that were taken from April to October in New York City. From these images, we operationalized a Green View Index (GVI) to identify very low, low, medium, and high visual density of greenness, respectively. We then paired this data with 1,414 commercial office transactions from Real Capital Analytics and 7,403 commercial office leases from CompStak in the marketplace over the 2010 to 2017 period.

Description of the Green View Index..
GSV vs. processed images.
Visually-perceived urban greenery.

What We Found:

Research Implications

  • Integration of street view images at a big data scale and deep learning image recognition algorithms allow for a new approach to human-scale measurement of urban greenery in the urban environment at full scale.
  • Results of the analysis document an 8.9% to 10.5% transaction price premium and a 5.6% to 7.8% rent premium for offices with Low to High GVI relative to those building transactions and leases spatially correlated with Very Low GVI.
  • The expanding role that image recognition has in the measurement of asset values.

Practical Implications

  • This research is the first to study street-level greenery from a commercial real estate standpoint. Corporate and institutional investment portfolios in office real estate are highly correlated with urban planning and institutional investment in the urban landscape.
  • Real estate developers are incentivized to align with landscape architecture and urban planning experts on this value-enhancing urban amenity.