Remote Sensing (Sep 2020)

Coral Reef Monitoring by Scuba Divers Using Underwater Photogrammetry and Geodetic Surveying

  • Erica Nocerino,
  • Fabio Menna,
  • Armin Gruen,
  • Matthias Troyer,
  • Alessandro Capra,
  • Cristina Castagnetti,
  • Paolo Rossi,
  • Andrew J. Brooks,
  • Russell J. Schmitt,
  • Sally J. Holbrook

DOI
https://doi.org/10.3390/rs12183036
Journal volume & issue
Vol. 12, no. 18
p. 3036

Abstract

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Underwater photogrammetry is increasingly being used by marine ecologists because of its ability to produce accurate, spatially detailed, non-destructive measurements of benthic communities, coupled with affordability and ease of use. However, independent quality control, rigorous imaging system set-up, optimal geometry design and a strict modeling of the imaging process are essential to achieving a high degree of measurable accuracy and resolution. If a proper photogrammetric approach that enables the formal description of the propagation of measurement error and modeling uncertainties is not undertaken, statements regarding the statistical significance of the results are limited. In this paper, we tackle these critical topics, based on the experience gained in the Moorea Island Digital Ecosystem Avatar (IDEA) project, where we have developed a rigorous underwater photogrammetric pipeline for coral reef monitoring and change detection. Here, we discuss the need for a permanent, underwater geodetic network, which serves to define a temporally stable reference datum and a check for the time series of photogrammetrically derived three-dimensional (3D) models of the reef structure. We present a methodology to evaluate the suitability of several underwater camera systems for photogrammetric and multi-temporal monitoring purposes and stress the importance of camera network geometry to minimize the deformations of photogrammetrically derived 3D reef models. Finally, we incorporate the measurement and modeling uncertainties of the full photogrammetric process into a simple and flexible framework for detecting statistically significant changes among a time series of models.

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