The internship project aim is to derive and classify geomorphic features from high-resolution seafloor data and to explore how these features vary with depth in the shallow and mesophotic zones along the Saudi Arabian coast of the Red Sea. The student will preprocess the multibeam bathymetry datasets collected across coral-dominated reef environments, generate digital elevation models (DEMs), and extract terrain attributes such as slope, curvature, Bathymetric Position Index (BPI) and rugosity. Building on these metrics, the project will identify and classify geomorphic features (e.g., terraces, slopes, ridges, depressions) and assess their distribution across depth zones. The study will contribute to understanding how geomorphological variability reflects seafloor organization in coral reef-associated settings, providing a baseline for future ROV explorations, long-term monitoring, and the identification of priority areas to be considered within marine spatial planning and protection strategies.

 - Preprocessed and gridded DEMs from the multibeam datasets.

- Classification of geomorphic features and their distribution across shallow vs mesophotic environments.

- Comparative maps and statistical analysis of geomorphological variability with depth.

- Final report and presentation discussing methods, results, limitations, and future applications.