Original Source

Reconstructing the Historical Expansion of Industrial Swine Production from Landsat Imagery

Scientific Reports

Volume: 12: 1736

2 FEB 2022

Montefiore, L. R., Nelson, N. G., Dean, A. & Sharara, M.

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From the source: "This work is supported by the North Carolina Sea Grant College Program Omnibus 2018-2021, award number NA18OAR4170069; the USDA National Institute of Food and Agriculture, Agriculture and Food Research Initiative, Educational Literacy Initiative’s Research and Extension Experiences for Undergraduates grant program, grant no. 2019-67032-29074/project accession no. 1018043; USDA National Institute of Food and Agriculture Hatch projects 1016068 and 1022103; and an Early-Career Research Fellowship from the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine. The content is solely the responsibility of the authors and does not necessarily represent the official views of North Carolina Sea Grant, the USDA, or the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine."

From the source: "The authors declare no competing interests."
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Summary

This study used satellite remote sensing to study concentrated animal feeding operations (CAFOs) and swine waste lagoons (SWLs) in South Carolina, USA. The findings suggest that most SWLs were built after 1990, but before restrictions were implemented in 1997. Many SWLs are built on watersheds. Moreover, many SWLs and CAFOs were classified as natural systems (such as forests or lakes) rather than lagoons. A strength of this study is that only images of the highest quality were used and this did not appear to substantially limit the data collected. The authors suggest that a limitation of this study was the SWLs had to be searched for on Google Earth by a person instead of a program, which opens a margin of human error. This study uncovered CAFO and SWL classification errors made by the authorities, which raises concerns about the amount of manure being produced within watersheds and the potential impacts of these errors, which can misguide environmental and ecological studies relying on such information.

In the USA, historical data on the period over which industrial swine farms have operated are usually only available at the county scale and released every 5 years via the USDA Census of Agriculture, leaving the history of the swine industry and its potential legacy effects on the environment poorly understood. We developed a changepoint-based workflow that recreates the construction timelines of swine farms, specifically by identifying the construction years of swine manure lagoons from historical Landsat 5 imagery for the period of 1984 to 2012. The study focused on the Coastal Plain of North Carolina, a major pork-producing state in the USA. The algorithm successfully predicted the year of swine waste lagoon construction (+ /− 1 year) with an accuracy of approximately 94% when applied to the study area. By estimating the year of construction of 3405 swine waste lagoons in NC, we increased the resolution of available information on the expansion of swine production from the county scale to spatially-explicit locations. We further analyzed how the locations of swine waste lagoons changed in proximity to water resources over time, and found a significant increase in swine waste lagoon distances to the nearest water feature across the period of record.