GoPros™ as an underwater photogrammetry tool for citizen science

Raoult, Vincent; David, Peter A.; Dupont, Sally F.; Mathewson, Ciaran; O’Neill, Samuel J.; Powell, Nicholas N.; Williamson, Jane E.

doi:10.7717/peerj.1960

Cited by 53 publications

(52 citation statements)

References 43 publications

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“…Agisoft software is a relatively affordable and user-friendly package that automatically adjusts images for lens distortion, corrects image colours, performs structure-from-motion reconstructions, and allows measurements of length, volume, and surface area. This software has now been used in several coral reef studies [8,[37][38][39].…”

Section: Analysesmentioning

confidence: 99%

“…Where the spiral technique was insufficient to cover the vertical surface of the larger bommies, a u-shaped coverage pattern was used. The aim was to obtain~80% overlap between images, which allowed good image alignment during image processing, and has previously been identified as a key problem area for constructing models [8]. There was no upper or lower limit to the number of images taken as the objective was to obtain complete photo coverage of the chosen bommie.…”

Section: Inter-individual Variability In Documenting Coral Bommiesmentioning

confidence: 99%

“…Images were captured using GoPro™ Hero 4 Black cameras set to continuously capture 12 MP JPEG images every 0.5 s as adapted from the method in Raoult et al [8]. As structure from motion requires a reference object with known dimensions to accurately measure an object, a 1.5 kg dive weight with known dimensions was placed next to each bommie.…”

Section: Inter-individual Variability In Documenting Coral Bommiesmentioning

confidence: 99%

“…The image capturing process was adapted from Gutierrez-Heredia et al [36] and Raoult et al [8]. Individual snorkelers swam in a clockwise or anticlockwise direction that allowed spiralling around the bommie, taking overlapping photographs at three main angles to provide good coverage of the object: 45 degrees, planar, and top-down.…”

Section: Inter-individual Variability In Documenting Coral Bommiesmentioning

confidence: 99%

“…While such survey techniques are effective, they are limited by the precision of their measurements and the ease of directly comparing data from successive years or months. Recently, structure from motion has become prevalent as another tool for reef monitoring [8][9][10][11]. Structure from motion is an image processing technique that allows construction of accurate 3D models from overlapping successive photographs taken at various angles.…”

Section: Introductionmentioning

confidence: 99%

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How Reliable Is Structure from Motion (SfM) over Time and between Observers? A Case Study Using Coral Reef Bommies

et al. 2017

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Recent efforts to monitor the health of coral reefs have highlighted the benefits of using structure from motion-based assessments, and despite increasing use of this technique in ecology and geomorphology, no study has attempted to quantify the precision of this technique over time and across different observers. This study determined whether 3D models of an ecologically relevant reef structure, the coral bommie, could be constructed using structure from motion and be reliably used to measure bommie volume and surface area between different observers and over time. We also determined whether the number of images used to construct a model had an impact on the final measurements. Three dimensional models were constructed of over twenty coral bommies from Heron Island, a coral cay at the southern end of the Great Barrier Reef. This study did not detect any significant observer effect, and there were no significant differences in measurements over four sampling days. The mean measurement error across all bommies and between observers was 15 ± 2% for volume measurements and 12 ± 1% for surface area measurements. There was no relationship between the number of pictures taken for a reconstruction and the measurements from that model, however, more photographs were necessary to be able to reconstruct complete coral bommies larger than 1 m 3 . These results suggest that structure from motion is a viable tool for ongoing monitoring of ecologically-significant coral reefs, especially to establish effects of disturbances, provided the measurement error is considered.

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Section: Analysesmentioning

confidence: 99%

Section: Inter-individual Variability In Documenting Coral Bommiesmentioning

confidence: 99%

Section: Inter-individual Variability In Documenting Coral Bommiesmentioning

confidence: 99%

Section: Inter-individual Variability In Documenting Coral Bommiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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How Reliable Is Structure from Motion (SfM) over Time and between Observers? A Case Study Using Coral Reef Bommies

et al. 2017

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Evaluating the efficacy of small‐scale marine protected areas for preserving reef health: A case study applying emerging monitoring technology

Bayley

Mogg

Purvis

et al. 2019

Aquatic Conservation

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1. Marine Protected Areas (MPAs) are widely used as management tools to conserve species and ecosystems at risk from human impact. Coastal managers often focus MPA designation on biogenic reef environments due to their value and sensitivity to damage. However, difficulties in enforcement and a lack of capacity to adequately monitor MPAs often make it hard for managers to assess the effectiveness of MPAs, particularly in under-resourced, low-income coastal countries. 2. Reef community data were collected at three long-term managed reserves within the Western Visayas region of the central Philippines in order to assess the state of reef community structure inside and outside of these small-scale locally managed MPAs. In addition, 3D structural data were captured using recently developed 'Structure from Motion' (SfM) photogrammetry techniques, demonstrating how multiple quantitative metrics of physical structural complexity and health can be recorded in such analyses. 3. These community-run MPAs were shown to be effective even when small (10-20 ha). Mean fish biomass density was five times greater within present-day protected sites, alongside significantly increased levels of fish diversity, richness, and size. No significant structural differences were observed inside and outside of MPAs, however, average reef rugosity, height, and roughness were significantly higher in unfished reefs compared to blast-fished reefs. Reef substrate complexity, coral composition, and level of management, were also shown to structure fish community assemblages, with the link between reef structure and fish richness / abundance disrupted outside of MPAs. 4. The SfM technique allows a greater range of quantitative morphometrics to be assessed than traditional methods and at relatively low cost. The technique is rapid, non-destructive and can be archived, increasing the value of data for managers wishing to quantify reef health and efficiently monitor benthic changes through time. We discuss both the limitations and benefits of this technology's future use.

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Deep Learning for Multilabel Classification of Coral Reef Conditions in the Indo‐Pacific Using Underwater Photo Transect Method

Shao,

Chen,

Magson

et al. 2024

Aquatic Conservation

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Because coral reef ecosystems face threats from human activities and climate change, coral reef conservation programmes are implemented worldwide. Monitoring coral health provides references for guiding conservation activities. However, current labour‐intensive methods result in a backlog of unsorted images, highlighting the need for automated classification. Few studies have simultaneously utilized accurate labels along with updated algorithms and datasets. This study aimed to create a dataset representing common coral reef conditions and associated stressors in the Indo‐Pacific. Concurrently, it assessed existing classification algorithms and proposed a new multilabel method for automatically detecting coral reef conditions and extracting ecological information. A dataset containing over 20,000 high‐resolution coral images of different health conditions and stressors was constructed based on the field survey. Seven representative deep learning architectures were tested on this dataset, and their performance was quantitatively evaluated using the F1 metric and the match ratio. Based on this evaluation, a new method utilizing the ensemble learning approach was proposed. The proposed method accurately classified coral reef conditions as healthy, compromised, dead and rubble; it also identified corresponding stressors, including competition, disease, predation and physical issues. This method can help develop the coral image archive, guide conservation activities and provide references for decision‐making for reef managers and conservationists. The proposed ensemble learning approach outperforms others on the dataset, showing state‐of‐the‐art (SOTA) performance. Future research should improve its generalizability and accuracy to support global coral reef conservation efforts.

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GoPros™ as an underwater photogrammetry tool for citizen science

Cited by 53 publications

References 43 publications

How Reliable Is Structure from Motion (SfM) over Time and between Observers? A Case Study Using Coral Reef Bommies

How Reliable Is Structure from Motion (SfM) over Time and between Observers? A Case Study Using Coral Reef Bommies

Evaluating the efficacy of small‐scale marine protected areas for preserving reef health: A case study applying emerging monitoring technology

Deep Learning for Multilabel Classification of Coral Reef Conditions in the Indo‐Pacific Using Underwater Photo Transect Method

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