A protocol for the large‐scale analysis of reefs using Structure from Motion photogrammetry

Bayley, Daniel T. I.; Mogg, Andrew O.M.

doi:10.1111/2041-210x.13476

Cited by 41 publications

(36 citation statements)

References 53 publications

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“…Underwater digital photogrammetry is a rapid survey protocol for large areas without the need for trained personnel in species identification (Chirayath and Instrella, 2019;Lechene et al, 2019;Price et al, 2019;Bayley and Mogg, 2020;Hernández-Landa et al, 2020). This protocol allows extracting not only cover and community metrics but also important demographic information on the size of the colonies and the spatial relationships in the benthic community (Edwards et al, 2017;Hernández-Landa et al, 2020).…”

Section: Comparisons Between Monitoring Protocolsmentioning

confidence: 99%

“…Underwater digital photogrammetry protocols (UWP) with different approaches have recently been used to address changes in the 3D structure associated with natural disturbances (Burns et al, 2015;Peck et al, 2021), assess patterns in the spatial distribution of reef-building corals (Edwards et al, 2017) and reef structural complexity (Burns et al, 2016;Price et al, 2019), and characterize the ecological structure and demographic characteristics of coral colonies (Capra et al, 2017;Edwards et al, 2017;Young et al, 2017;Bianchi, 2019;Lechene et al, 2019;Neyer et al, 2019;Bayley and Mogg, 2020;Burns et al, 2020;Hernández-Landa et al, 2020;Nocerino et al, 2020;Rossi et al, 2020). Results on comparisons between UWP and monitoring protocols to assess reefs characteristics obtained from sites in the Indian and Pacific ocean have been varied.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Standard Caribbean Coral Reef Monitoring Protocols and Underwater Digital Photogrammetry to Characterize Hard Coral Species Composition, Abundance and Cover

et al. 2021

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The precise assessing and monitoring of coral reefs are necessary to address and understand the threats and changes in coral communities. With the development of new technologies and algorithms for image processing, new protocols like underwater photogrammetry are implemented to study these ecosystems. This study compares the main ecological metrics for reef condition assessment, obtained with an underwater digital photogrammetry protocol (UWP) and traditional sampling design simulations in coral reefs of the Cozumel Reefs National Park. Three orthomosaics (380 m2) per reef on six fringing reefs were constructed, and the hard coral community characterized using a Geographic Information System (GIS). The orthomosaics were also used as a basis to simulate transect lines and obtain data on the hard coral community according to the video transect (VT) protocol, point intercept (PIT) protocol, and the Atlantic and Gulf Rapid Reef Assessment (AGRRA) protocol. Higher colony abundance, species richness, and lower coral cover estimates (p < 0.05) were obtained with the UWP. This protocol was also sensitive to small sized species. All the sampling designs showed similar capability to identify dominant species in terms of colony abundance and coral cover. The VT, PIT, and AGGRA showed similar coral cover values (p > 0.05), which seems to indicate that these sampling designs overestimate this important metric. Our results will help to understand and integrate the observations obtained with UWP with long-term data obtained with commonly used monitoring protocols in the Caribbean region.

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Section: Comparisons Between Monitoring Protocolsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of Standard Caribbean Coral Reef Monitoring Protocols and Underwater Digital Photogrammetry to Characterize Hard Coral Species Composition, Abundance and Cover

et al. 2021

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“…Data collection and the reconstruction of 3D models for other habitats will depend on topographic features (e.g., vertical relief), currents and/or surge (in marine environments) as both will affect the number of images needed to acquire an accurate model. To ensure quality results, 3-D reconstructed models should be created from mostly static scenes using a high-resolution camera, and with ground control points (i.e., coded targets) strategically placed around areas of interest; for more information on performing SfM in underwater scenes in particular, we refer interested readers to the Supplementary Information section and (Ferrari et al, 2016;Young et al, 2018;Bayley and Mogg, 2020;Hopkinson et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Classifying 3-D Models of Coral Reefs Using Structure-From-Motion and Multi-View Semantic Segmentation

et al. 2021

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Benthic quadrat surveys using 2-D images are one of the most common methods of quantifying the composition of coral reef communities, but they and other methods fail to assess changes in species composition as a 3-dimensional system, arguably one of the most important attributes in foundational systems. Structure-from-motion (SfM) algorithms that utilize images collected from various viewpoints to form an accurate 3-D model have become more common among ecologists in recent years. However, there exist few efficient methods that can classify portions of the 3-D model to specific ecological functional groups. This lack of granularity makes it more difficult to identify the class category responsible for changes in the structure of coral reef communities. We present a novel method that can efficiently provide semantic labels of functional groups to 3-D reconstructed models created from commonly used SfM software (i.e., Agisoft Metashape) using fully convolutional networks (FCNs). Unlike other methods, ours involves creating dense labels for each of the images used in the 3-D reconstruction and then reusing the projection matrices created during the SfM process to project semantic labels onto either the point cloud or mesh to create fully classified versions. When quantitatively validating the classification results we found that this method is capable of accurately projecting semantic labels from image-space to model-space with scores as high as 91% pixel accuracy. Furthermore, because each image only needs to be provided with a single set of dense labels this method scales linearly making it useful for large areas or high resolution-models. Although SfM has become widely adopted by ecologists, deep learning presents a steep learning curve for many. To ensure repeatability and ease-of-use, we provide a comprehensive workflow with detailed instructions and open-sourced the programming code to assist others in replicating our methodology. Our method will allow researchers to assess precise changes in 3-D community composition of reef habitats in an entirely novel way, providing more insight into changes in ecological paradigms, such as those that occur during coral-algae shifts.

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“…After filtering out photos containing non‐target objects or with non‐vertical camera orientations, 390 photos were used for modeling. Fish were masked out of the images manually, and SfM processing was accomplished using Agisoft Metashape Pro following the general protocols, module sequence, and settings (Bayley & Mogg, 2020). Scaling was established using 19 X/Y (horizontal) control points from the Autonomous Reef Monitoring Structures (ARMS) instruments deployed through the study area [each ARMS plate is 22.5 × 22.5 cm, see locations in Figure 2b].…”

Section: Field Site and Methodsmentioning

confidence: 99%

How Consistent Are Estimates of Roughness Parameters on a Rough Coral Reef?

et al. 2021

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Turbulent boundary layers, created by flws interacting with the rough topography of coral reefs, are important to many aspects of reef function and health (Davis et al., 2021). For example, turbulent boundary layers are important to coral health by supporting nutrient uptake (Lowe & Falter, 2015). For an unstratified, turbulent flow over a rough bottom, the boundary layer takes the form of the law-of-the-wall (Pope, 2012):where u(z) is the horizontal velocity at height z above the bed, u * is the friction velocity, z 0 is the roughness height, d is the displacement height, and we adopt the von Kármán constant κ = 0.41 following Nepf (2011). The friction velocity can also be calculated directly from the Reynolds stresses at the bed Abstract Coral reefs are hydrodynamically rough, creating turbulent boundary layers that transport and mix various scalars that impact reef processes and also can be used to monitor reef health. Often reef boundary layer characteristics derived from a single instrument are assumed to accurately represent the study site. This approach relies on two assumptions: first, that the boundary layer is relatively homogeneous across the area of interest, and second, that two instruments displaced in space or with different spatiotemporal resolution would produce similar results when sampling the same flow. We deployed four velocimeters over a 15 × 20 m reef at 10 m depth in the Chagos Archipelago. The site had a 1 m tidal range, and waves were primarily locally generated wind waves with H rms < 0.5 m. Depth-averaged currents were typically 0.2 m/s. Friction velocities derived directly from Reynolds stress measurements by fitting the law of the wall show agreement between instruments (pairwise coefficients of determination R 2 ranged from 0.53 to 0.86). Thus, the boundary layer appears to be spatially homogeneous, at least at the scale of our array, and it appears that in the present case friction velocities from one instrument are indeed generally representative of the site. We calculate drag coefficients using curve-fitting and Structure-from-Motion photogrammetry, and while we find general agreement between estimates one instrument in particular produces drag coefficients an order of magnitude larger in comparison. Hence, some variability between instruments was observed, notably when high-resolution instruments measured localized flow features.

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A protocol for the large‐scale analysis of reefs using Structure from Motion photogrammetry

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 41 publications

References 53 publications

Comparison of Standard Caribbean Coral Reef Monitoring Protocols and Underwater Digital Photogrammetry to Characterize Hard Coral Species Composition, Abundance and Cover

Comparison of Standard Caribbean Coral Reef Monitoring Protocols and Underwater Digital Photogrammetry to Characterize Hard Coral Species Composition, Abundance and Cover

Classifying 3-D Models of Coral Reefs Using Structure-From-Motion and Multi-View Semantic Segmentation

How Consistent Are Estimates of Roughness Parameters on a Rough Coral Reef?

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