Assessment of the utility of underwater hyperspectral imaging for surveying and monitoring coral reef ecosystems

Matthew S Mills; Mischa Ungermann; Guy Rigot; Joost den Haan; Javier X Leon; Tom Schils

doi:10.1038/s41598-023-48263-6

Back

Assessment of the utility of underwater hyperspectral imaging for surveying and monitoring coral reef ecosystems

Journal article

Open access

Peer reviewed

Assessment of the utility of underwater hyperspectral imaging for surveying and monitoring coral reef ecosystems

Matthew S Mills, Mischa Ungermann, Guy Rigot, Joost den Haan, Javier X Leon and Tom Schils

Scientific Reports, Vol.13, pp.1-15

2023

DOI: https://doi.org/10.1038/s41598-023-48263-6

PMCID: PMC10689744

PMID: 38036628

Files and links (2)

pdf

Assessment of the utility3.61 MBDownload View

Published Version Open Access CC BY V4.0

url

https://doi.org/10.1038/s41598-023-48263-6View

Published Version

Abstract

coral reefs

imaging

imaging and sensing

marine biology

tropical ecology

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.

Details

Title: Assessment of the utility of underwater hyperspectral imaging for surveying and monitoring coral reef ecosystems
Authors: Matthew S Mills (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Mischa Ungermann (Author) - PlanBlue GmBH (Germany)
Guy Rigot (Author) - PlanBlue GmBH (Germany)
Joost den Haan (Author) - PlanBlue GmBH (Germany)
Javier X Leon (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Tom Schils (Author) - University of Guam
Publication details: Scientific Reports, Vol.13, pp.1-15
Publisher: Nature Publishing Group
Date published: 2023
DOI: 10.1038/s41598-023-48263-6
ISSN: 2045-2322
PMID: 38036628; PMC10689744
Copyright note: © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Data Availability: Synthesized data used in downstream analyses can be found within the Supplementary Information files. However, due to substantial file and dataset sizes, the full (unsynthesized) datasets generated and/or analyzed during this study are available from the corresponding author on reasonable request.
Organisation Unit: School of Science, Technology and Engineering; Sustainability Research Cluster
Language: English
Record Identifier: 99982998902621
Output Type: Journal article

Metrics

3 File views/ downloads

57 Record Views