Using very high resolution remote sensing for the management of coral reef fisheries: Review and perspectives

Hamel, Mélanie A.; Andréfouët, Serge

doi:10.1016/j.marpolbul.2010.07.002

Cited by 68 publications

(41 citation statements)

References 67 publications

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“…Alternatively, swath acoustics can generate digital elevation models with horizontal resolutions of a few square meters [20,21], from which various metrics of habitat complexity, such as slope or surface rugosity (the ration between surface area and planar area), can be quantified across thousands of square meters [22]. Although useful for many applications, these methods are incapable of characterizing underwater structures at high-resolutions (cm-scale) [23,24].…”

Section: Introductionmentioning

confidence: 99%

Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling

Ferrari

McKinnon²,

et al. 2016

Remote Sensing

103

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Coral reef habitat structural complexity influences key ecological processes, ecosystem biodiversity, and resilience. Measuring structural complexity underwater is not trivial and researchers have been searching for accurate and cost-effective methods that can be applied across spatial extents for over 50 years. This study integrated a set of existing multi-view, image-processing algorithms, to accurately compute metrics of structural complexity (e.g., ratio of surface to planar area) underwater solely from images. This framework resulted in accurate, high-speed 3D habitat reconstructions at scales ranging from small corals to reef-scapes (10s km 2 ). Structural complexity was accurately quantified from both contemporary and historical image datasets across three spatial scales: (i) branching coral colony (Acropora spp.); (ii) reef area (400 m 2 ); and (iii) reef transect (2 km). At small scales, our method delivered models with <1 mm error over 90% of the surface area, while the accuracy at transect scale was 85.3%˘6% (CI). Advantages are: no need for an a priori requirement for image size or resolution, no invasive techniques, cost-effectiveness, and utilization of existing imagery taken from off-the-shelf cameras (both monocular or stereo). This remote sensing method can be integrated to reef monitoring and improve our knowledge of key aspects of coral reef dynamics, from reef accretion to habitat provisioning and productivity, by measuring and up-scaling estimates of structural complexity.

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Section: Introductionmentioning

confidence: 99%

Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling

Ferrari

McKinnon²,

et al. 2016

Remote Sensing

103

View full text Add to dashboard Cite

show abstract

“…The difference between theie values plays the role of relationships of these parameters, and root mean square deviation serves as indicator of variability of values of this difference. Given this specificity, the working hypothesis is to be complemented by implication, the content of which is reflected in formulas (9), (10).…”

Section: Obtained Results Of Research Into Systemic Aspects Of Relatimentioning

confidence: 99%

“…Paper [3] refers to possibilities of using analysis of space photos for keeping records of marmots in steppe regions (these animals can also be a potential reservoir of dangerous infectious diseases). In article [10], the coral reef ecosystems were explored with the use of remote methods. These ecosystems are in great danger due to global climate change that can significantly alter the nature of distribution of waterfowlpotential reservoirs for avian influenza.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Mathematical modeling of systemic colorometric parameters unmasking wild waterfowl

Balym

Vуsotska

Pecherska

et al. 2017

EEJET

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“…Predicted spatial inventories of coral reef fisheries resources have multiple advantages for fisheries management and conservation [54], including improved information for prioritizing locations for conservation and management through marine spatial planning and the ability to assess potential changes to fish communities following large disturbances that alter reef habitat structure. However, their utility depends on the accuracies of the model predictions, which themselves depend on the accuracy of mapped predictor variables as well as the statistical relationships between predictors and response variables.…”

Section: Discussionmentioning

confidence: 99%

Mapping Fish Community Variables by Integrating Field and Satellite Data, Object-Based Image Analysis and Modeling in a Traditional Fijian Fisheries Management Area

et al. 2011

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Abstract:The use of marine spatial planning for zoning multi-use areas is growing in both developed and developing countries. Comprehensive maps of marine resources, including those important for local fisheries management and biodiversity conservation, provide a crucial foundation of information for the planning process. Using a combination of field and high spatial resolution satellite data, we use an empirical procedure to create a bathymetric map (RMSE 1.76 m) and object-based image analysis to produce accurate maps of geomorphic and benthic coral reef classes (Kappa values of 0.80 and 0.63; 9 and 33 classes, respectively) covering a large (>260 km 2 ) traditional fisheries management area in Fiji. From these maps, we derive per-pixel information on habitat richness, structural complexity, coral cover and the distance from land, and use these variables as input in models to predict fish species richness, diversity and biomass. We show that random forest models outperform five other model types, and that all three fish community variables can be satisfactorily predicted from the high spatial resolution satellite data. We also show geomorphic zone to be the most important predictor on average, with secondary contributions from a range of other variables including benthic class, depth, distance from land, and live coral cover mapped at coarse spatial scales, suggesting that data with lower spatial resolution and lower cost may be sufficient for spatial predictions of the three fish community variables. OPEN ACCESSRemote Sens. 2011, 3 461

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Using very high resolution remote sensing for the management of coral reef fisheries: Review and perspectives

Cited by 68 publications

References 67 publications

Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling

Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling

Mathematical modeling of systemic colorometric parameters unmasking wild waterfowl

Mapping Fish Community Variables by Integrating Field and Satellite Data, Object-Based Image Analysis and Modeling in a Traditional Fijian Fisheries Management Area

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