Crowdsourcing Arctic Navigation Using Multispectral Ice Classification & GNSS

Tyler Reid, Todd Walter and Per Enge, Ananda Fowler

Abstract: Safe marine navigation in the Arctic is becoming more important with a growing interest in the region in recent years. With the summer Arctic sea ice extent having decreased by 50% since 1980, this now opening waterway has given rise to serious interest in commercial activities in the Arctic. There are several navigational challenges that face ships operating in Arctic waters. Sea charts are known to be untrustworthy, navigational equipment can be problematic, and there is the constant danger of multi-year and glacial ice collisions. Here we focus on the threat of ice. Knowledge of its whereabouts is crucial to the safe planning of routes and in the avoidance of sometimes-fatal collisions. With increased traffic and without proper detection systems in place, there is a danger of accidents in the Arctic that may result in loss of life or have severe environmental ramifications. Here we propose a modernized system which offers improvements in the two major components of the current ice mitigation strategy, namely, on the ship-based monitoring side and on the ship-to-ship aiding side. Ship-based monitoring today is a largely manual process which requires a skilled and experienced crew to interpret radar data and scan the area visually to correctly identify dangerous ice. This relies heavily on the use of expert lookouts, as radar is known to fall short of the requirements needed to reliably detect all forms of hazardous ice. Ship-to-ship aiding exists today in the form of organizations such as the North American Ice Service (NAIS) where icebergs and ice conditions are reported in part by passing ships. However, most ice reports are based on visual sightings whose accuracy is likely not high. Here, we propose crowdsourcing ice navigation based on a GNSS data registration system. In this scenario, ice detection and classification is done robustly and automatically based on a redundant multispectral system. This data is then geo-referenced using GNSS, enabling reliable ship-to-ship aiding in systematic way. The high integrity sharing of ice data offers a framework in which to perform path planning in a reliable and automated way, finding the safest route with the available information and relying less on the expertise of the crew.
Published in: Proceedings of the 27th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2014)
September 8 - 12, 2014
Tampa Convention Center
Tampa, Florida
Pages: 707 - 721
Cite this article: Reid, Tyler, Walter, Todd, Enge, Per, Fowler, Ananda, "Crowdsourcing Arctic Navigation Using Multispectral Ice Classification & GNSS," Proceedings of the 27th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2014), Tampa, Florida, September 2014, pp. 707-721.
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