Remmers, Tiny, Boutros, Nader, Wyatt, Mathew, Gordon, Sophie, Toor, Maren, Roelfsema, Chris, Fabricius, Katharina, Grech, Alana, Lechene, Marine, and Ferrari Legorreta, Renata (2025) RapidBenthos: Automated segmentation and multi‐view classification of coral reef communities from photogrammetric reconstruction. Methods in Ecology and Evolution, 16 (2). pp. 427-441.

Preview

PDF (Published Version) - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview

Abstract

Underwater photogrammetry is routinely used to monitor large areas of complex and heterogeneous ecosystems, such as coral reefs. However, deriving data on benthic components (i.e. sand, rubble, coral and algae) from photogrammetry products has remained challenging due to the highly time-consuming process of manual data extraction.

We developed a machine learning approach to quantify benthic community composition in coral reefs from orthomosaics, which requires no manual delineation of benthic components for training or implementation. The current study presents RapidBenthos, an automated workflow that segments and classifies large-area images. Our pipeline (1) uses a pre-trained segmentation model, eliminating the need for manually generated fine-scale segmented training data, and (2) classifies the resulting segments from multiple views using the underlying survey images, allowing for classification to fine taxonomic levels.

Within a test photomosaic built from a coral reef area of 40 m−2, the model automatically detected 43 different benthic classes. Validation resulted in an overall classification accuracy of 0.96 and a segmentation accuracy of 0.87, when compared to a manually digitised replica. The RapidBenthos workflow was 195 times faster than manual segmentation and classification. Additional validation of 524 Acropora coral colonies from 11 additional test plots resulted in a segmentation accuracy of 0.92 and classification accuracy of 0.88 to the coarser ‘Acropora’ group.

RapidBenthos has the capability to extract an unprecedented level of data from photomosaics of coral reefs or other complex environments, allowing to sustainably scale photogrammetric monitoring technique both in replicate and survey extent, which consequently can lead to new research questions and more informed ecosystem management.

Item ID:	86410
Item Type:	Article (Research - C1)
ISSN:	2041-210X
Copyright Information:	© 2024 The Author(s). Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution inany medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Date Deposited:	28 Jul 2025 22:48
FoR Codes:	41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410401 Conservation and biodiversity @ 100%
SEO Codes:	18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180504 Marine biodiversity @ 100%
Downloads:	Total: 2 Last 12 Months: 2
	More Statistics