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Inicio  /  Applied Sciences  /  Vol: 12 Par: 21 (2022)  /  Artículo
ARTÍCULO
TITULO

Maritime Traffic Evaluation Using Spatial-Temporal Density Analysis Based on Big AIS Data

Yoon-Ji Kim    
Jeong-Seok Lee    
Alessandro Pititto    
Luigi Falco    
Moon-Suk Lee    
Kyoung-Kuk Yoon and Ik-Soon Cho    

Resumen

For developing national maritime traffic routes through the coastal waters of Korea, the customary maritime traffic flow must be accurately identified and quantitatively evaluated. In this study, the occupancy time of ships in cells was calculated through a density analysis based on automatic identification system data. The density map was statistically created by logarithmically transforming the density values and adopting standard deviation-based stretch visualization to increase the normality of the distribution. Many types of traffic routes such as open-sea, coastal, inland, and coastal access routes were successfully identified; moreover, the stretch color ramp ratio was reduced to identify routes having relatively high density. Adopting a single standard deviation and demonstrating the top 25% of color ramps, the analysis afforded the main routes through which customary traffic flows. This novel density analysis method and statistical visualization method is expected to be used for developing national maritime traffic routes and should ultimately contribute to maritime safety. Moreover, it provides a scientific means and simulator for determining the navigation area and analyzing conflicts with other activities in marine spatial planning.

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