International Journal of Digital Earth · 2022 · 23 citations · 72 references
ComputingComputer ScienceMarine EngineeringArtificial IntelligenceBig Data AnalyticsMachine LearningIce MonitoringIntelligent Transportation SystemsNavigation PlanningRoute PlanningSea Ice Remote SensingDeep Reinforcement LearningDeep Reinforcement Learning For NavigationReal-time NavigationRoute InferenceShip NavigationShip Trajectory PlanningSynthetic Aperture RadarSynthetic Aperture Radar Sea Ice Analysis
The potential of Arctic routes (ARs) has attracted global attention, and exploiting the Arctic has become an important strategy for many countries. However, there are still some challenges for ships sailing in Arctic ice zones, including harsh marine environments and the insufficient service capacity of sea ice information service systems. To better understand the route changes in the Arctic and extract real-time ship navigation routes, we developed an online interactive route planning system (RouteView) for ships sailing in the Arctic based on big Earth data. RouteView includes two main features: (1) an online calculation interface is provided for optimal routes along the Arctic Northeast Passage (NEP) 60 days into the future by utilizing reinforcement learning (RL) based on sea ice and meteorological data, and (2) an online ice-water classification is established based on synthetic aperture radar (SAR) data and deep learning to help users extract the sea ice distribution in real time. This work can potentially enhance the safety of shipping navigation along the NEP and improve information extraction methods for ARs.
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Engineering, Educational Psychology, Cognitive Psychology +7