The goal of FAST-CAST 2 is to make a decisive contribution to transforming data from satellite-based earth observation and weather forecasts into route suggestions through ice-covered areas on request from a ship via app. AI techniques are used to accelerate the underlying processes and modern web technologies such as Progressive Web Apps are used to interact with the user.
FAST-CAST 2 will combine findings from FAST-CAST and MAPBORealis and transfer them into the development and validation of a comprehensive route optimization system for ice-covered areas.
The project is led by the Zentrum für Technomathematik at Universität Bremen. The consortium includes project partners Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) and EOMAP GmbH & Co. KG (EOMAP).
In the frames of FAST-CAST2, DNPS will work together with DLR in validating ice drift forecasts from TOPAZ4 model, and will extend the PRIIMA algorithm, to assimilate ice drift data from the higher resolution model neXtSIM. Another important aspect is to integrate the route optimization user interface, within the IcySea app, in a concrete and intuitive way, providing the best possible user experience.
DLR will perform ice drift forecast validations, using their newly developed algorithm based on the phase correlation method for high-resolution ice drift tracing, from Sentinel-1 image pairs. Further they aim to develop new algorithms, to detect and indicate ice convergence zones. Those are dangerous areas that may even trap a ship in the ice.
EOMAP will provide bathymetric information in polar regions, which are not covered as as good as in the middle latitudes. They foresee to use multispectral satellite data and lidar.
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