Cloud Solution For Satellite Seafloor Mapping

The 4S project will quickly analyse information such as satellite-derived bathymetry data (shown) to derisk marine site characterisation activities in the shallow water zone. Photo: Agri-Food and Biosciences Institute, Belfast

Posted on January 14, 2021

An EU co-funded research and innovation project will develop a remote solution for global satellite derived seafloor mapping.

The three-year 4S (Satellite Seafloor Survey Suite) EOMAP-led project will develop an online cloud-based solution that will use highly automated earth observation algorithms and workflows to remotely map and monitor seafloor habitats, morphology and shallow water bathymetry.

Dr. Knut Hartmann, 4S project coordinator and COO of EOMAP, which is leading the project, said: “The aim of 4S is to achieve a seamless integration of satellite-data analytics into marine and coastal workflows. We’re combining recent advances in satellite sensors, data analytics and cloud infrastructure to benefit marine reporting, monitoring and surveying methods.”

Rapid analysis

4S will leverage artificial intelligence, physics models, and satellite and airborne data to derisk marine site characterisation activities in the shallow water zone by quickly analysing seafloor properties using less personnel and equipment.

Fugro will lead the project’s business and integration actions, and its hydrographers and Geo-data specialists will evaluate the solution via several use cases around the globe.

Dhira Adhiwijna, Fugro’s 4S project manager, said: “Fugro is honoured to be part of an exciting EU innovation that could result in faster and safer Geo-data insights for our energy and infrastructure clients. Upon completion, 4S will be integrated into our high-speed hydrography offering and provide innovative solutions that will also derisk marine site characterisation activities.”

The 4S consortium includes experts from the fields of satellite data analytics, hydrography and biology.

By Rebecca Jeffrey

Source: maritimejournal