Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts
Climate change and subsequent retreat of sea ice favor the increase of maritime traDc in the polar regions. Despite the growing importance of the ice-covered Arctic Ocean for all types of global shipping and the availability of massive Earth Observation (EO) and weather data archives, navigational d...
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ftdlr:oai:elib.dlr.de:190362 2024-05-19T07:33:17+00:00 Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts Belter, H. Jakob Rabenstein, Lasse Schmitz, Bernhard Kountouris, Panagioti Eis, Christine Bathmann, Martin Frost, Anja Wiehle, Stefan Knauer, Kim Büskens, Christof 2023 https://elib.dlr.de/190362/ https://www.arcticfrontiers.com/ unknown Belter, H. Jakob und Rabenstein, Lasse und Schmitz, Bernhard und Kountouris, Panagioti und Eis, Christine und Bathmann, Martin und Frost, Anja und Wiehle, Stefan und Knauer, Kim und Büskens, Christof (2023) Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts. Arctic Frontiers 2023, 2023-01-30 - 2023-02-02, Tromsø, Norway. SAR-Signalverarbeitung Konferenzbeitrag NonPeerReviewed 2023 ftdlr 2024-04-25T01:03:56Z Climate change and subsequent retreat of sea ice favor the increase of maritime traDc in the polar regions. Despite the growing importance of the ice-covered Arctic Ocean for all types of global shipping and the availability of massive Earth Observation (EO) and weather data archives, navigational decision making is still limited. This is due to the fact that manual data pick up by the ship crews continues to be next to impossible for at least the following two reasons. (1) Communication bandwidth is limited in Arctic regions and (2) the conversion of such data into navigational decisions is inherently a big data process. The FastCast-2 project develops innovative solutions to enhance the value of satellite-based EO and weather data. Furthermore, we process that data into near-real time and on-demand route suggestions for stakeholders transiting through or around ice-infested waters. AI-techniques are used to accelerate underlying processing steps and state-of-the-art web technologies like ‘Progressive Web Apps’ are utilized for user interaction. The International Maritime Organization’s Polar Code requires ships to have up-to-date ice information on board when heading towards the polar regions. Although the ice is retreating, sea ice, icebergs and uncharted bathymetry remain hazardous for modern day shipping in the Arctic. The FastCast-2 consortium strives to combine improved sea ice drift forecasts with up-to-theminute ice and weather information, which are processed into continuously updated route suggestions. These route suggestions will also avoid shallow areas detected by satellite-derived bathymetry. This kind of service will not only help ships to fulfill the Polar Code requirements. It will also advance digitization of the shipping industry and enable ship crews and their companies to find the safest, fastest and most fuel-effient routes in and around ice-covered waters. Conference Object Arctic Arctic Arctic Ocean Climate change Iceberg* Sea ice ice covered waters German Aerospace Center: elib - DLR electronic library |
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Open Polar |
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German Aerospace Center: elib - DLR electronic library |
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SAR-Signalverarbeitung |
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SAR-Signalverarbeitung Belter, H. Jakob Rabenstein, Lasse Schmitz, Bernhard Kountouris, Panagioti Eis, Christine Bathmann, Martin Frost, Anja Wiehle, Stefan Knauer, Kim Büskens, Christof Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts |
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SAR-Signalverarbeitung |
description |
Climate change and subsequent retreat of sea ice favor the increase of maritime traDc in the polar regions. Despite the growing importance of the ice-covered Arctic Ocean for all types of global shipping and the availability of massive Earth Observation (EO) and weather data archives, navigational decision making is still limited. This is due to the fact that manual data pick up by the ship crews continues to be next to impossible for at least the following two reasons. (1) Communication bandwidth is limited in Arctic regions and (2) the conversion of such data into navigational decisions is inherently a big data process. The FastCast-2 project develops innovative solutions to enhance the value of satellite-based EO and weather data. Furthermore, we process that data into near-real time and on-demand route suggestions for stakeholders transiting through or around ice-infested waters. AI-techniques are used to accelerate underlying processing steps and state-of-the-art web technologies like ‘Progressive Web Apps’ are utilized for user interaction. The International Maritime Organization’s Polar Code requires ships to have up-to-date ice information on board when heading towards the polar regions. Although the ice is retreating, sea ice, icebergs and uncharted bathymetry remain hazardous for modern day shipping in the Arctic. The FastCast-2 consortium strives to combine improved sea ice drift forecasts with up-to-theminute ice and weather information, which are processed into continuously updated route suggestions. These route suggestions will also avoid shallow areas detected by satellite-derived bathymetry. This kind of service will not only help ships to fulfill the Polar Code requirements. It will also advance digitization of the shipping industry and enable ship crews and their companies to find the safest, fastest and most fuel-effient routes in and around ice-covered waters. |
format |
Conference Object |
author |
Belter, H. Jakob Rabenstein, Lasse Schmitz, Bernhard Kountouris, Panagioti Eis, Christine Bathmann, Martin Frost, Anja Wiehle, Stefan Knauer, Kim Büskens, Christof |
author_facet |
Belter, H. Jakob Rabenstein, Lasse Schmitz, Bernhard Kountouris, Panagioti Eis, Christine Bathmann, Martin Frost, Anja Wiehle, Stefan Knauer, Kim Büskens, Christof |
author_sort |
Belter, H. Jakob |
title |
Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts |
title_short |
Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts |
title_full |
Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts |
title_fullStr |
Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts |
title_full_unstemmed |
Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts |
title_sort |
optimized route suggestions for ships in polar regions using ai- based processing, earth observation data, and model forecasts |
publishDate |
2023 |
url |
https://elib.dlr.de/190362/ https://www.arcticfrontiers.com/ |
genre |
Arctic Arctic Arctic Ocean Climate change Iceberg* Sea ice ice covered waters |
genre_facet |
Arctic Arctic Arctic Ocean Climate change Iceberg* Sea ice ice covered waters |
op_relation |
Belter, H. Jakob und Rabenstein, Lasse und Schmitz, Bernhard und Kountouris, Panagioti und Eis, Christine und Bathmann, Martin und Frost, Anja und Wiehle, Stefan und Knauer, Kim und Büskens, Christof (2023) Optimized route suggestions for ships in polar regions using AI- based processing, Earth Observation data, and model forecasts. Arctic Frontiers 2023, 2023-01-30 - 2023-02-02, Tromsø, Norway. |
_version_ |
1799471364633001984 |