Evidence map›Paper›PMID 30150709›Full record

ArticleScientific reports2018

Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna.

Ines Dumke, Autun Purser, Yann Marcon, Stein M Nornes, Geir Johnsen, Martin Ludvigsen, Fredrik Søreide

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ines DumkeDepartment of Marine Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. idumke@geomar.de.ORCID 0000-0003-0323-8578
Autun PurserAlfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany.
Yann MarconAlfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany.ORCID 0000-0002-1686-8045
Stein M NornesDepartment of Marine Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.ORCID 0000-0002-8487-0024
Geir JohnsenCentre for Autonomous Marine Operations and Systems, Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Martin LudvigsenDepartment of Marine Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Fredrik SøreideDepartment of Marine Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

Funding

Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 03F0707A-GEC | Seventh Framework Programme (European Union Seventh Framework Programme) 604500Norges Forskningsråd (Research Council of Norway) 223254Norges Forskningsråd (Research Council of Norway) 250228
6 · The paper itself

Abstract

Identification of benthic megafauna is commonly based on analysis of physical samples or imagery acquired by cameras mounted on underwater platforms. Physical collection of samples is difficult, particularly from the deep sea, and identification of taxonomic morphotypes from imagery depends on resolution and investigator experience. Here, we show how an Underwater Hyperspectral Imager (UHI) can be used as an alternative in situ taxonomic tool for benthic megafauna. A UHI provides a much higher spectral resolution than standard RGB imagery, allowing marine organisms to be identified based on specific optical fingerprints. A set of reference spectra from identified organisms is established and supervised classification performed to identify benthic megafauna semi-autonomously. The UHI data provide an increased detection rate for small megafauna difficult to resolve in standard RGB imagery. In addition, seafloor anomalies with distinct spectral signatures are also detectable. In the region investigated, sediment anomalies (spectral reflectance minimum at ~675 nm) unclear in RGB imagery were indicative of chlorophyll a on the seafloor. Underwater hyperspectral imaging therefore has a great potential in seafloor habitat mapping and monitoring, with areas of application ranging from shallow coastal areas to the deep sea.

Indexed as

Aquatic OrganismsEcosystemOceans and Seas

Identifiers

PMID30150709
PMCPMC6110793

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.