Title
Examining the distribution of green roofs in New York City through a lens of social, ecological, and technological filters
Author(s)
Treglia, Michael L.; McPhearson, Timon; Sanderson, Eric W.; Yetman, Greg; Maxwell, Emily Nobel
Published
2022
Publisher
Ecology and Society
Abstract
Green roofs provide multiple benefits including reducing the urban heat island effect, absorbing stormwater and air pollution, and serving as habitat for wildlife. However, many cities have not taken advantage of green roofs as a nature-based solution. In New York City (NYC), approximately 20% of the landscape is covered by buildings, thus rooftops present a substantial opportunity for expanding green infrastructure. Spatial data on green roofs are critical for understanding their abundance and distribution, what filters may drive spatial patterns, and who benefits from them. We describe the development of a green roof dataset for NYC based on publicly available data and classification of aerial imagery from 2016. Of the over one million buildings in NYC, we found only 736 with green roofs (<0.1%), although there may have been others we did not detect. These green roofs are not evenly distributed in NYC - they are most common in midtown and downtown Manhattan, while most other areas have few to none. Green roofs tend to be more prevalent in parts of NYC with combined sewer systems, but some such areas, and those with the most heat-vulnerable communities, have few if any despite their potential to help ameliorate stormwater and urban heat challenges. Though green roofs are providing some benefits within NYC, we anticipate they are filtered based on dynamics of infrastructure, institutions, and perceptions, rather than targeted to address climate and weather-related challenges. There is substantial opportunity in NYC to increase green roofs, and equity of them. The dataset we developed is publicly available and can serve as a baseline for tracking these assets through time, while supporting further research, conversations, and policies related to the benefits and distribution of green roofs. The underlying methods can also be applied to help fill similar data gaps in other cities.
Keywords
cities; green infrastructure; green roofs; mapping; social-ecological-technical filters; urban remote sensing; urban systems
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PUB35937