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Abstract

Urban agriculture, including peri-urban farming, can nourish around one billion city dwellers and provide multiple social, economic, and environmental benefits. However, these benefits depend on various factors and are debated. Therefore, we used machine learning to semi-automate a systematic review of the existing literature on urban agriculture. It started with around 76,000 records for initial screening based on a broad keyword search strategy. We applied the topic modeling approach to systematically understand various aspects of urban agriculture based on the full text of around 1450 relevant publications. Urban agriculture literature covers 14 topics, clustered into 11 themes related to urban agriculture forms, their multi-functionalities, and their underlying challenges. These forms are small-scale ground-based and building-integrated systems. The multifunctionalities include food, livelihoods, health benefits, social space, green infrastructure, biodiversity, and ecosystem services. Therefore, promoting urban agriculture requires accounting for its multi-functionalities, besides food provisioning,and encouraging efficient and sustainable practices.