IKTPLUSS-IKT og digital innovasjon

The Arctic is undergoing the most rapid changes in the climate system worldwide, demonstrated by the thinning and reduction of sea ice, the melting of ice sheets and glaciers, thawing of permafrost, and an increased possibility for extreme weather events and other hazards. While the role of these Arctic changes in increasing risks of extreme weather events remains strongly debated, these interlinked processes are expected to increase the chance of natural hazards connected to unstable sea ice conditions and unexpected occurrences of icebergs. Such rapid and hard to predict changes pose a significant risk for shipping activities in this region, whether it be cargo, fisheries or tourism. Therefore, improved access to new and customised data products from innovative combinations of available in-situ measurements, remote sensing imagery and forecasting models is critical to further development of safe and sustainable Arctic shipping. The overall objective of the Digital Arctic Shipping project is to develop a suite of data products in collaboration with Arctic shipping companies and local authorities and to demonstrate the use of these products on vessels traveling in ice infested areas. This includes using drone mounted sensors custom-built for Arctic operations, in combination with near real-time data from satellites, and automatic identification of ice dynamics patterns (divergence, convergence). Examples of products include maps of ice types, ridges, leads and motion, which are all essential parameters for navigation in sea ice. Products will be transmitted to vessels using the best available satellite communication networks and used together with data collected on board (e.g. Automated Weather Stations (AWS)) and data supplied by other actors (e.g. Automatic Identification System (AIS)). The project has participated in two field research cruises north of Svalbard, the CAATEX 2020 field experiment and the UAK 2021 scientific cruise. During these cruises, project personnel collected data using drones, ship-borne radar and by physical measurements on the ice. Drones were used to collect high-resolution images over different types of ice, in the same area as the physical ice measurements and in the area surrounding the vessel. During CAATEX 2020, a total of 17 ice stations with ice cores and measurements of salinity and conductivity of the ice were collected. In addition, a Ku-band radar was used to collect radar images of the ice conditions around the vessel. During UAK 2021, a total of 7 ice stations with ice cores and measurements of temperature, salinity and density of the ice were collected. A series of photographs were taken for both cruises to further document the ice conditions at the ice station locations and along the route. Data from the ice stations will be used for validation of the drone data and in the construction of a 3D model of the ice using drone photogrammetry. During the summer of 2020, a series of test flights with a larger fixed-wing drone was conducted along the coast of Norway. This included testing take-off and landing from a vessel without a flight deck. These tests have continued in 2021, to prepare for use in research cruises later in the project where the ice conditions do not allow for such operations on the ice, or the vessel is prohibited from making stops along the way for drone take-off and landing operations. Work on data processing analysis is progressing well, with a focus on classification of sea ice in drone imagery using machine learning (ML) techniques. These classification algorithms will ultimately run in the on-board computing device of the drones. For efficient testing, a framework has been set up that enables plug-and-play testing of ML models on a newly developed sensor payload. Initial work on testing this ML framework in the drones has started.

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.