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Abstract:
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Community gardens, urban farms, and locally grown food are becoming increasingly popular in urban areas of the United States. These operations tend to be widely dispersed, small and have higher turnover than large production agricultural operations. Thus, it is difficult to obtain precise estimates for their numbers. In 2015, USDA's National Agricultural Statistics Service (NASS) collaborated with the Multi-Agency Collaborative Environment (MACE) to explore a new approach to identify urban agricultural operations. A pilot study was conducted within the city limits of Baltimore MD. An algorithm combining satellite imagery; social media feeds; and other publicly available data was used to identify possible agricultural operations. A sample was selected from the resulting list and interviews were conducted with the selected operation's operators. Coverage of the MACE list was compared to that of the NASS list frame using a list obtained from the City of Baltimore. In this paper, the methods used by MACE and NASS to identify urban operations are presented. Results from this pilot study are discussed, and some of the statistical challenges in calculating valid estimates addressed.
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