The interpretation of particle size, shape, and carbon flux of marine particle images is strongly affected by the choice of particle detection algorithm

Giering, Sarah L. C. ORCID: https://orcid.org/0000-0002-3090-1876; Hosking, Brett; Briggs, Nathan ORCID: https://orcid.org/0000-0003-1549-1386; Iversen, Morten H.. 2020 The interpretation of particle size, shape, and carbon flux of marine particle images is strongly affected by the choice of particle detection algorithm. Frontiers in Marine Science, 7, 564. 10.3389/fmars.2020.00564

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Abstract/Summary

In situ imaging of particles in the ocean are rapidly establishing themselves as powerful tools to investigate the ocean carbon cycle, including the role of sinking particles for carbon sequestration via the biological carbon pump. A big challenge when analysing particles in camera images is determining the size of the particle, which is required to calculate carbon content, sinking velocity and flux. A key image processing decision is the algorithm used to decide which part of the image forms the particle and which is the background. However, this critical analysis step is often unmentioned and its effect rarely explored. Here we show that final flux estimates can easily vary by an order of magnitude when selecting different algorithms for a single dataset. We applied a range of static threshold values and 11 different algorithms (seven threshold and four edge detection algorithms) to particle profiles collected by the LISST-Holo system in two contrasting environments. Our results demonstrate that the particle detection method does not only affect estimated particle size but also particle shape. Uncertainties are likely exacerbated when different particle detection methods are mixed, e.g., when datasets from different studies or devices are merged. We conclude that there is a clear need for more transparent method descriptions and justification for particle detection algorithms, as well as for a calibration standard that allows intercomparison between different devices.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.3389/fmars.2020.00564
ISSN:	2296-7745
Date made live:	19 Nov 2020 10:12 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/528984

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