OOS 52-7
Urban agriculture in New York City: Maps, measurements, and citizen science

Wednesday, August 12, 2015: 3:40 PM
328, Baltimore Convention Center
Clare Sullivan, Agriculture and Food Security Center, The Earth Institute, Columbia University, Palisades, NY
Background/Question/Methods

Urban agriculture in New York City (NYC) varies widely, but is predominantly informal and small scale. It ranges from community and school gardens to privately financed commercial rooftop farms. Despite a recent rapid expansion in NYC urban agriculture, there is a significant data gap. Even basic metrics, such as the number and location of gardens and farms are not readily available. Gardeners face constraints unique to the urban environment, but have little guidance on topics such as appropriate growing mediums, advantages of different container styles, or appropriate crop varieties. There is growing interest in reviewing municipal policies with respect to urban agriculture and to allocate grant funding and support in this area, but limited understanding of what is needed as well as associated economic and ecological benefits and costs. I evaluate several NYC initiatives that seek to address this data gap based on utilization, data utility and quality, and scalability. These initiatives range from traditional agricultural trials to social networks for organizing access to growing spaces and utilize tools such as geospatial data, mobile data collection, and citizen science methods. 

Results/Conclusions

All of the projects offer insight into simple, low-cost ways in which other metropolitan areas could correct similar data gaps and improve understanding of the role of agriculture in cities.  There are some data quality limitations, common in citizen science projects; however, data on simple metrics, such as spatial extent, crop diversity and yield data, are robust and participation by gardeners and farmers in the projects is high. It is notable that the most data rich projects, including Farming Concrete, 596acres, Feedback Farms are grassroots projects with very small budgets and are the driving forces behind closing the data gap. There has been very little state/city led data collection.