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Deep learning to map concentrated animal feeding operations

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  • Cassandra Handan-Nader

    (Stanford University
    Stanford University)

  • Daniel E. Ho

    (Stanford University
    Stanford University
    Stanford Institute for Economic Policy Research)

Abstract

Enforcement of environmental law depends critically on permitting and monitoring intensive animal agricultural facilities, known in the United States as ‘concentrated animal feeding operations’ (CAFOs). The current legal landscape in the United States has made it difficult for government agencies, environmental groups and the public to know where such facilities are located. Numerous groups have, as a result, conducted manual, resource-intensive enumerations based on maps or ground investigation to identify facilities. Here we show that applying a deep convolutional neural network to high-resolution satellite images offers an effective, highly accurate and lower cost approach to detecting CAFO locations. In North Carolina, the algorithm is able to detect 589 additional poultry CAFOs, representing an increase of 15% from the baseline that was detected through manual enumeration. We show how the approach scales over geography and time, and can inform compliance and monitoring priorities.

Suggested Citation

  • Cassandra Handan-Nader & Daniel E. Ho, 2019. "Deep learning to map concentrated animal feeding operations," Nature Sustainability, Nature, vol. 2(4), pages 298-306, April.
    • Handle: RePEc:nat:natsus:v:2:y:2019:i:4:d:10.1038_s41893-019-0246-x
    DOI: 10.1038/s41893-019-0246-x
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    Cited by:

    1. Xian Sun & Dongshuo Yin & Fei Qin & Hongfeng Yu & Wanxuan Lu & Fanglong Yao & Qibin He & Xingliang Huang & Zhiyuan Yan & Peijin Wang & Chubo Deng & Nayu Liu & Yiran Yang & Wei Liang & Ruiping Wang & C, 2023. "Revealing influencing factors on global waste distribution via deep-learning based dumpsite detection from satellite imagery," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    2. Hollas, C.E. & Bolsan, A.C. & Chini, A. & Venturin, B. & Bonassa, G. & Cândido, D. & Antes, F.G. & Steinmetz, R.L.R. & Prado, N.V. & Kunz, A., 2021. "Effects of swine manure storage time on solid-liquid separation and biogas production: A life-cycle assessment approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).

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