Abstract
The automatic identification system (AIS) was developed to support the safety of marine traffic. In ice-covered seas, the ship speeds extracted from AIS data vary with ice conditions that are simultaneously reflected by features in synthetic aperture radar (SAR) images. In this study, the speed variation was related to the SAR features and the results were applied to generate a chart of expected speeds from the SAR image. The study was done in the Gulf of Bothnia in March 2013 for ships with ice class IA Super that are able to navigate without icebreaker assistance. The speeds were normalized to dimensionless units ranging from 0 to 10 for each ship. As the matching between AIS and SAR was complicated by ice drift during the time gap (from hours to two days), we calculated a set of local statistical SAR features over several scales. Random forest tree regression was used to estimate the speed. The accuracy was quantified by mean squared error and by the fraction of estimates close to the actual speeds. These depended strongly on the route and the day. The error varied from 0.4 to 2.7 units2 for daily routes. Sixty-five percent of the estimates deviated by less than one speed unit and 82% by less than 1.5 speed units from the AIS speeds. The estimated daily mean speeds were close to the observations. The largest speed decreases were provided by the estimator in a dampened form or not at all. This improved when the ice chart thickness was included as a predictor.
Highlights
Ships navigating in ice-covered sea areas need ice information to support their operations
We defined that the estimate was close to the automatic identification system (AIS) speed if their difference was less than 1 unit
We presented an approach that uses position and speed data from the AIS messages of ice-going ships to translate synthetic aperture radar (SAR) images over ice cover to ship speed maps
Summary
Ships navigating in ice-covered sea areas need ice information to support their operations. In the Baltic Sea, operative ice information includes daily ice charts, ice model forecasts, and ice thickness charts provided by the national ice services, in our case by the Finnish Ice Service (FIS). The production of the information relies strongly on synthetic aperture radar (SAR) imagery, both Sentinel-1 and Radarsat-2 imagery, typically obtained once or twice a day from each sea area. The level ice thickness chart is a supporting operative SAR-based product [1]. The product refines the level ice thickness information of the ice charts using SAR-based segmentation. The product has been operative for several years It is validated annually using ship reports and more extensively in reference [2]
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