Sea ice concentration and thickness are important parameters for the calculations of ice actions and their effects on Arctic offshore structures and for the evaluation of icebreaker performance. Various methods exist nowadays to monitor these parameters, ranging from geophysical scale to local scale. During the Oden Arctic Technology Research Cruise 2015 (OATRC’ 15), we installed both Ice Concentration and Ice Thickness cameras and developed corresponding algorithms to achieve real time quantification of ice concentration and visual estimation of ice thickness information. For the ice concentration analysis, we utilized both the global Otsu method to categorize an image into two regions (black water and white ice); and the K-means method to identify more regions based on the gray scale from the image. With the methods, we conducted a case study by analyzing the ice concentration in a selected time window. In the case study, we include both dry ice (in white color) and wet ice (in gray color, generally composed of ice rubbles, young ice, and melt ponds) as ice region for the K-means method. The K-means method yields higher ice concentration values in comparison to the global Otsu method, in which, melt ponds/young ice was frequently mistaken as open water. It turns out that the K-means method enables more flexibility to cope with the complicated ice environment by separating the image into more regions that can be included as ice in an ice concentration analysis. For the ice thickness camera, the intention was to capture the events while a broken ice piece is tilted, next to the ship side, and expose its thickness region to the camera. In this paper, we developed an automatic tracking algorithm to sift these events out from all the images taken by the Ice Thickness acquisition system. After projecting a grid with physical length onto the image, the ice thickness information can be visually quantified. We compared the ice thickness obtained from the Ice Thickness camera and that obtained by an Electro-Magnetic inductive device in a selected time window. The results agree well with each other. Considering the advantages and disadvantages of each method, this demonstrates the benefits of combining redundant approaches for obtaining the ice thickness information with a higher degree of confidence.

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