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Automated identification of intensive animal production locations from aerial photography

KJ Sheffield,JC Hunnam,TN Cuzner,EM Morse-McNabb,SM Sloan,J. Nunan,J. Smith,W. Harvey,H. Lewis

Published 2018 in Australian Veterinary Journal

ABSTRACT

OBJECTIVE Successful control of an emergency animal disease outbreak requires the timely and accurate identification of properties of interest. The identification of commercial piggeries within study areas in the Goulburn-Murray Irrigation District in Victoria, Australia, is used to demonstrate the innovative application of object-based image analysis (OBIA) techniques for the identification of intensive animal production land uses, to improve the accuracy of existing datasets. METHODS Characteristics of infrastructure and landscape features were combined to form a commercial piggery identification algorithm. These criteria were applied to recent aerial photography that had been classified using OBIA techniques. The results were then compared with three datasets containing known commercial piggery locations and visually checked by roadside surveys. RESULTS The OBIA technique identified 21 potential piggery locations across three study areas, 14 of which were identified in existing databases. Of the 7 additional sites, 4 were dairy properties, 1 was a cropping and sheep property and 2 were previously undocumented piggery locations. CONCLUSIONS The OBIA approach has potential of OBIA for identifying the locations of commercial piggeries. Further development and testing will determine how generic this approach is in terms of industry type and operation size. The method described is cost-effective, automated and repeatable, and could be used to regularly update existing databases by analysing newly acquired aerial imagery to identify possible land use changes. This would improve the reliability of currently available data and increase the effectiveness of a biosecurity response during an emergency animal disease outbreak.

PUBLICATION RECORD

  • Publication year

    2018

  • Venue

    Australian Veterinary Journal

  • Publication date

    2018-08-27

  • Fields of study

    Agricultural and Food Sciences, Medicine, Biology, Environmental Science

  • Identifiers
    DOI 10.1111/avj.12732PMID 30152061
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar, PubMed

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