4.7 Article

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

期刊

REMOTE SENSING
卷 8, 期 2, 页码 -

出版社

MDPI
DOI: 10.3390/rs8020113

关键词

surface rugosity; off-the-shelf; computer vision; photogrammetry; structure from motion; coral reefs; topographic maps; habitat structural complexity; surface area; volume

资金

  1. WCS-RLP
  2. Khaled bin Sultan Living Oceans Foundation
  3. CoNaCYT Mexico
  4. University of Exeter
  5. Queensland University of Technology
  6. University of Queensland
  7. XL Catlin Seaview Survey
  8. Global Change Institute

向作者/读者索取更多资源

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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