Next-Gen Mapping and Monitoring of Coral Reefs with SLAM and SfM

Traditional approaches to characterize and quantify benthic communities and their changes rely on 1D or 2D surveys conducted by divers within a prescribed area. A limited number of survey sites and a relatively small portion of a reef surface can be characterized in a typical day of work, and the identification of the key invertebrates relies on experts and is notoriously time consuming.  The Red Sea Development Company (TRSDC) is one of Saudi’s premiere “gigaprojects”. It aims to develop a world-class, hyper-luxury resort complex in the Al-Wajh lagoon, a unique site featuring rich and complex framework geological and biological habitats. As the TRSDC is committed to protecting the natural environment, surveys of the site’s coral reefs are planned at an unprecedented scale and new challenges arise in terms of data acquisition and analyses. The overarching project objective is to develop a framework for large-scale, semi-autonomous implementation of Simultaneous Localization and Mapping (SLAM) and Structure from Motion (SfM) of coral reefs to facilitate: 1) establish a large scale and high resolution 3D quantitative coral community baseline assessment; 2) develop a mechanism for high-resolution detection of change in various environmental indicators; 3) pioneer a large-scale demonstration of automation of the various components (surveys, coral identification, and 3D reconstruction). These goals will be attained through a combination of field surveys, supervised classification of videos, SfM to create 3D reconstructions of reefs and individual corals, and SLAM with autonomous underwater vehicles (AUVs). The key innovation will be to test the capacity of the AUV to capture an SfM dataset.  In addition to reconstructing the 3D mesh, machine learning will be used to gradually automate the identification of corals within a reconstruction. Repeated surveys of a site (aided by SLAM and the installation of permanent guidance “beacons”) will provide unprecedented scientific insights, such as colony-specific growth rates or the ability to detect subtle early warning signs in coral health.

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