The Digital Arctic Shipping project will develop new sea ice data products and visualisation services for Arctic shipping. Automated and intelligent sensors will be used to collect data in difficult and dangerous navigation areas. The consortium has the following observation technologies available for the project: drones carrying multispectral or radar sensors, single or dual-band ship radars, in situ measurements of snow and ice, and a broad range of satellite sensors (e.g. synthetic aperture radar, passive microwave and optical) from Chinese, European and US space programmes. The heterogeneity and vast amount of data generated by these sensors requires scalable ICT frameworks to efficiently manage and extract key sea ice parameters that can be translated into useful information for Arctic shipping. The chosen technologies and tools will be co-developed together with ship operators with extensive knowledge of navigation in Arctic regions. Specifically, we will apply novel machine learning techniques such as deep learning for automatic detection of riskful conditions. The derived data products will be organised in a data management system and distributed to targeted user groups using standard protocols and communication networks. We will demonstrate the developed data collection, management, analysis and distribution services through case studies targeted at the Arctic shipping industry. Each case study will be co-developed by scientists, local authorities and shipping companies and result in new data products and visualisation services for supporting safer Arctic shipping. Demonstrations of products and services will focus on cargo traffic in the Northern Sea Route and other ship traffic areas in the Arctic. The project partners have collaborated on Arctic and Climate science for the past 15 years and will strengthen and extend this collaboration to provide digital services for customised data delivery for Arctic shipping.
Project leader: Torill Hamre
Institution: STIFTELSEN NANSEN SENTER FOR MILJØ OG FJERNMÅLING