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An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system

Supporting Files


Filetype [PDF - 16.54 MB]

Details

  • Journal Title:
    PLOS ONE
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Measurements of body size and mass are fundamental to pinniped population management and research. Manual measurements tend to be accurate but are invasive and logistically challenging to obtain. Ground-based photogrammetric techniques are less invasive, but inherent limitations make them impractical for many field applications. The recent proliferation of unmanned aerial systems (UAS) in wildlife monitoring has provided a promising new platform for the photogrammetry of free-ranging pinnipeds. Leopard seals (Hydrurga leptonyx) are an apex predator in coastal Antarctica whose body condition could be a valuable indicator of ecosystem health. We aerially surveyed leopard seals of known body size and mass to test the precision and accuracy of photogrammetry from a small UAS. Flights were conducted in January and February of 2013 and 2014 and 50 photogrammetric samples were obtained from 15 unrestrained seals. UAS-derived measurements of standard length were accurate to within 2.01 +/- 1.06%, and paired comparisons with ground measurements were statistically indistinguishable. An allometric linear mixed effects model predicted leopard seal mass within 19.40 kg (4.4% error for a 440 kg seal). Photogrammetric measurements from a single, vertical image obtained using UAS provide a noninvasive approach for estimating the mass and body condition of pinnipeds that may be widely applicable.
  • Source:
    PLOS ONE
  • DOI:
  • Pubmed Central ID:
    PMC5706667
  • Document Type:
  • Place as Subject:
  • Rights Information:
    CC BY
  • Compliance:
    PMC
  • Download URL:
  • File Type:
    Filetype[PDF - 16.54 MB]
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:d687187356a63dec9d0909f89d3b62bef1637ff6cced0b0523e31bfa58851e7406614edf70990097c6ef37acde1387de59a8f7d6be1a63ae39e04f64efe58141
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