Dataset Information

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

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.

SUBMITTER: Dumke I

PROVIDER: S-EPMC6110793 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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

Dumke Ines I Purser Autun A Marcon Yann Y Nornes Stein M SM Johnsen Geir G Ludvigsen Martin M Søreide Fredrik F

Scientific reports 20180827 1

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 s ...[more]

PMID: 30150709

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Project description:Technological innovations that improve the speed, scale, reproducibility, and accuracy of monitoring surveys will allow for a better understanding of the global decline in tropical reef health. The DiveRay, a diver-operated hyperspectral imager, and a complementary machine learning pipeline to automate the analysis of hyperspectral imagery were developed for this purpose. To evaluate the use of a hyperspectral imager underwater, the automated classification of benthic taxa in reef communities was tested. Eight reefs in Guam were surveyed and two approaches for benthic classification were employed: high taxonomic resolution categories and broad benthic categories. The results from the DiveRay surveys were validated against data from concurrently conducted photoquadrat surveys to determine their accuracy and utility as a proxy for reef surveys. The high taxonomic resolution classifications did not reliably predict benthic communities when compared to those obtained by standard photoquadrat analysis. At the level of broad benthic categories, however, the hyperspectral results were comparable to those of the photoquadrat analysis. This was particularly true when estimating scleractinian coral cover, which was accurately predicted for six out of the eight sites. The annotation libraries generated for this study were insufficient to train the model to fully account for the high biodiversity on Guam's reefs. As such, prediction accuracy is expected to improve with additional surveying and image annotation. This study is the first to directly compare the results from underwater hyperspectral scanning with those from traditional photoquadrat survey techniques across multiple sites with two levels of identification resolution and different degrees of certainty. Our findings show that dependent on a well-annotated library, underwater hyperspectral imaging can be used to quickly, repeatedly, and accurately monitor and map dynamic benthic communities on tropical reefs using broad benthic categories.

Project description:BackgroundIn zoology, species descriptions conventionally rely on invasive morphological techniques, frequently leading to damage of the specimens and thus only a partial understanding of their structural complexity. More recently, non-destructive imaging techniques have successfully been used to describe smaller fauna, but this approach has so far not been applied to identify or describe larger animal species. Here, we present a combination of entirely non-invasive as well as minimally invasive methods that permit taxonomic descriptions of large zoological specimens in a more comprehensive manner.ResultsUsing the single available representative of an allegedly novel species of deep-sea cephalopod (Mollusca: Cephalopoda), digital photography, standardized external measurements, high-field magnetic resonance imaging, micro-computed tomography, and DNA barcoding were combined to gather all morphological and molecular characters relevant for a full species description. The results show that this specimen belongs to the cirrate octopod (Octopoda: Cirrata) genus Grimpoteuthis Robson, 1932. Based on the number of suckers, position of web nodules, cirrus length, presence of a radula, and various shell characters, the specimen is designated as the holotype of a new species of dumbo octopus, G. imperator sp. nov. The digital nature of the acquired data permits a seamless online deposition of raw as well as derived morphological and molecular datasets in publicly accessible repositories.ConclusionsUsing high-resolution, non-invasive imaging systems intended for the analysis of larger biological objects, all external as well as internal morphological character states relevant for the identification of a new megafaunal species were obtained. Potentially harmful effects on this unique deep-sea cephalopod specimen were avoided by scanning the fixed animal without admixture of a contrast agent. Additional support for the taxonomic placement of the new dumbo octopus species was obtained through DNA barcoding, further underlining the importance of combining morphological and molecular datasets for a holistic description of zoological specimens.

Dataset Information

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

Publications

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

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