Abstract
Abstract. Artificial reefs provide an efficient way to improve marine life abundance in the oceans, including growth on the structure itself. Photogrammetric methods provide suitable tools to measure marine growth. This paper focusses on cubic reefs placed in Western Australia. The capturing platform featured a photogrammetric multi-sensor system for unmanned underwater vehicles attached to a low-cost vehicle BlueROV2. The multi-sensor system and its photogrammetric data captured was calibrated, adjusted and analyzed employing a structure-from-motion processing pipeline. Novel automated image masking techniques were developed and applied to the data to significantly reduce noise in the derived dense point clouds. Results show improvements of signal to noise ratio of more than 50 %, while maintaining a complete representation of the observed artificial reef.
Highlights
Artificial reefs are purpose-built submerged structures that enable marine life, such as corals, oysters or algae to settle on, and attract fish to feed and shelter from predators
It can be observed that the mean C2M distance remained constantly low for all numbers of images with the Machine learning (ML) method, whereas the image processing (IP) method and no masking showed a significant increase in C2M mean distance with increasing image numbers
In the full dataset with three cameras, a total number of 547 images were filtered using this method. This can be used to select and reduce the number of images for SfM, to prevent processing datasets with too many images. This contribution provides a workflow from calibration and acquisition to the analysis of photogrammetric data from artificial reefs
Summary
Artificial reefs are purpose-built submerged structures that enable marine life, such as corals, oysters or algae to settle on, and attract fish to feed and shelter from predators. Several artificial reefs sized 3 × 3 × 3 m3 (Figure 1) have been deployed off Western Australia’s coast in order to avoid recreational overfishing and create new fishing spots around Western Australia (Florisson et al, 2018). The long term goal of this study is to develop and test a method for estimating the volume of marine biomass growing on underwater artificial reefs. This paper’s contribution aims to develop a workflow to process photogrammetric data from two or three synchronized cameras in an underwater environment with spatial structures
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