MagicBathy: Multimodal multitAsk learninG for MultIsCale BATHYmetric mapping in shallow waters

About the Research Programme

MagicBathy is a research project funded by the European Commission for the period 2023-2025. It is funded under the HORIZON Europe MSCA Postdoctoral Fellowships - European Fellowships (GA 101063294) and it is hosted by the Remote Sensing and Image Analysis Group at the Faculty of Electrical Engineering and Computer Science, Technische Universit├Ąt Berlin, Germany. A secondment will be also take plase at the Visual Recognition Group of Czech technical university in Prague, Czech Republic.


Accurate, detailed and high-frequent bathymetry, coupled with the important visual and semantic information, is crucial for the undermapped shallow coastal areas being affected by intense climatological and anthropogenic pressures. Regular UAV and satellite imagery have the potential to frequently and consistently map those areas to different extents and detail, providing ground breaking key information. However, optical properties of water severely affect images and refraction is the main factor affecting their geometry. Current Structure from Motion (SfM) based solutions for refraction correction are slow and costly. Satellite Derived Bathymetry (SDB) methods deliver faster results over huge shallow areas albeit in lower spatial resolution, failing to handle non-homogeneous seabeds. Recent methods based on Convolutional Neural Networks (CNNs) are mostly dedicated to satellite images, failing to address the challenges of shallow waters, being also inefficient for UAV images, preventing higher resolution results. MagicBathy will establish an advanced deep learning framework for low-cost shallow water mapping. Frameworks, models and results will be published in open access, enabling the rapid progress in shallow water mapping worldwide.


Panagiotis Agrafiotis

Postdoctoral Fellow

Begum Demir


Giorgos Tolias

Assistant Professor
Secondment Supervisor