ArticleScientific reports2018
Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna.
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.
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Who cites it
5 citing papers in PubMed.
- Automated underwater image analysis reveals sediment patterns and megafauna distribution in the tropical Atlantic.Scientific reports · 2025Article
- Hardware-accelerated integrated optoelectronic platform towards real-time high-resolution hyperspectral video understanding.Nature communications · 2024Article
- Hyperspectral data as a biodiversity screening tool can differentiate among diverse Neotropical fishes.Scientific reports · 2021Article
- Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review.Sensors (Basel, Switzerland) · 2020Review
- Application of Hyperspectral Imaging to Underwater Habitat Mapping, Southern Adriatic Sea.Sensors (Basel, Switzerland) · 2019Article
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Authors and funding
7 authors.
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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.
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