Estimating 3-dimensional colony surface area of field corals

Courtney, Lee A.; Fisher, William S.; Raimondo, Sandy; Oliver, Leah M.; Davis, William P.

doi:10.1016/j.jembe.2007.06.021

Cited by 55 publications

(75 citation statements)

References 23 publications

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“…Underwater photogrammetry has proven to be a relatively accurate technique for morphological measurements of hemispherical scleractinian corals with studies demonstrating mean differences in 3D surface areas of 0.85% [25], <5% [27], 13% [26], and 1%-17% [28] and differences in volume of 1.7% [26], 3% [29], to 5%-9% [28]. Accuracy does seem to decrease for more complex branching and disc growth forms with errors in volume of 8% [28] and 17%-24% [29] and in surface area of 2% [28] and 12%-78% [27].…”

Section: Introductionmentioning

confidence: 99%

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

et al. 2015

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Abstract:In tropical reef ecosystems corals are the key habitat builders providing most ecosystem structure, which influences coral reef biodiversity and resilience. Remote sensing applications have progressed significantly and photogrammetry together with application of structure from motion software is emerging as a leading technique to create three-dimensional (3D) models of corals and reefs from which biophysical properties of structural complexity can be quantified. This enables the addressing of a range of important marine research questions, such as what the role of habitat complexity is in driving key ecological processes (i.e., foraging). Yet, it is essential to assess the accuracy and precision of photogrammetric measurements to support their application in mapping, monitoring and quantifying coral reef form and structure. This study evaluated the precision (by repeated modeling) and accuracy (by comparison with laser reference models) of geometry and structural complexity metrics derived from photogrammetric 3D models of marine benthic habitat at two ecologically relevant spatial extents; individual coral colonies of a range of common morphologies and patches of reef area of 100s of square metres. Surface rugosity measurements were generally precise across all morphologies and spatial extents with average differences in the geometry of replicate models of 1-6 mm for coral colonies and 25 mm for the reef area. Precision decreased with complexity of the coral morphology, with metrics for small massive corals being the most precise (1% coefficient of variation (CV) in surface rugosity) and metrics for bottlebrush corals being the least precise (10% CV in surface rugosity). There was no indication however that precision was related to complexity for the patch-scale modelling. The 3D geometry of coral models differed by only 1-3 mm from laser reference models. However, high spatial variation in these differences around the model led to a consistent underestimation of surface rugosity values for all morphs of between 8% and 37%. This study highlights the utility of several off-the-shelf photogrammetry tools for the measurement of structural complexity across a range of scales relevant to ecologist and managers. It also provides important information on the accuracy and precision of these systems which should allow for their targeted use by non-experts in computer vision within these contexts.

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Section: Introductionmentioning

confidence: 99%

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

et al. 2015

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“…The laser scanning methodology had first been employed to measure skeleton surface areas of coral colonies (Courtney et al 2007;Holmes et al 2008). As our data show, laser scanning is a very accurate method for measuring surface area of small coral fragments, where minute imprecision in surface area evaluations could significantly distort the experiment's results, an obstacle associated with other methods.…”

Section: Discussionmentioning

confidence: 99%

“…3A-D to 25.4 × 34.5 cm. Regular laser scanning equipment, while known as good and reliable (Courtney et al 2007), is costly and inaccessible to routine laboratory work. However, the desktop laser scanner we used is compact (about the size of a cereal box), easy to operate, and economically feasible.…”

Section: Discussionmentioning

confidence: 99%

“…The scanning preparation process is simple and time-saving (Table 1). There is no need for marking any reference points on the skeleton (Courtney et al 2007), and both scanning and alignment are automatic. Operation time is difficult to evaluate because of the scarcity of data.…”

Section: Discussionmentioning

confidence: 99%

“…Although they are capable of high-resolution measurement of corals' surface areas, the main disadvantage of the above tools is their inaccessibility to routine laboratory work. Another recent approach is the use of a laser scanner for measuring coral surface area (Courtney et al 2007;Holmes et al 2008). Although laser scanning is described as "the most accurate method for surface area determination of complex shapes," it is costly and best suitable for measuring entire coral colonies (Courtney et al 2007).…”

Section: Introductionmentioning

confidence: 99%

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Three‐dimensional laser scanning as an efficient tool for coral surface area measurements

Raz-Bahat

Faibish

Mass

et al. 2009

Limnology & Ocean Methods

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In scleractinian corals, as in many sessile colonial organisms, surface area serves as the prime descriptor for standardization and quantification of physiological and biochemical parameters. The complexity of colonial architecture, however, complicates measurement of surface area, yielding less than satisfactory results for the established methodologies. Here, we used a 3D desktop laser scanner for accurate measurements of skeletal surface area of various coral fragments. The original 127-µm accuracy of the scanner was tested on modules with increasing complexity. It showed a linear (R 2 = 0.912), but relatively small, increase of up to 9.67% accuracy error in complex modules. The scanner's maximum credibility error in repeated measurements was only 1.67%, representing an average error of 0.87 ± 0.66%. We compared the scanner's measured surface area results with those of four established methods: wax coating, foil paper wrapping, methylene blue dipping, and caliper measurements. In all methods, credibility and accuracy errors pointed to the superiority of the new method. Laser scanning is rapid (minimum 10 min per scan), efficient, easy to operate, and economically feasible as a common bench tool.

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Characterization of measurement errors using structure‐from‐motion and photogrammetry to measure marine habitat structural complexity

Bryson

Ferrari

Figueira

et al. 2017

Ecology and Evolution

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Habitat structural complexity is one of the most important factors in determining the makeup of biological communities. Recent advances in structure‐from‐motion and photogrammetry have resulted in a proliferation of 3D digital representations of habitats from which structural complexity can be measured. Little attention has been paid to quantifying the measurement errors associated with these techniques, including the variability of results under different surveying and environmental conditions. Such errors have the potential to confound studies that compare habitat complexity over space and time. This study evaluated the accuracy, precision, and bias in measurements of marine habitat structural complexity derived from structure‐from‐motion and photogrammetric measurements using repeated surveys of artificial reefs (with known structure) as well as natural coral reefs. We quantified measurement errors as a function of survey image coverage, actual surface rugosity, and the morphological community composition of the habitat‐forming organisms (reef corals). Our results indicated that measurements could be biased by up to 7.5% of the total observed ranges of structural complexity based on the environmental conditions present during any particular survey. Positive relationships were found between measurement errors and actual complexity, and the strength of these relationships was increased when coral morphology and abundance were also used as predictors. The numerous advantages of structure‐from‐motion and photogrammetry techniques for quantifying and investigating marine habitats will mean that they are likely to replace traditional measurement techniques (e.g., chain‐and‐tape). To this end, our results have important implications for data collection and the interpretation of measurements when examining changes in habitat complexity using structure‐from‐motion and photogrammetry.

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Estimating 3-dimensional colony surface area of field corals

Cited by 55 publications

References 23 publications

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

Three‐dimensional laser scanning as an efficient tool for coral surface area measurements

Characterization of measurement errors using structure‐from‐motion and photogrammetry to measure marine habitat structural complexity

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