Abstract:  Current practice shows that working with bridge waterway automatic identification system (AIS) data often does not lead to insight but rather confusion because large data volume without further being processed is hard to understand. In order to deal with this issue, bridge waterway of Wuhan section in Yangtze River was selected as research area for the study of AIS visualization model and humancomputer interaction method. Additionally, two dimensional kernel density estimation approach was adopted in the heatmap generation to overcome the defects of traditional grid method. Furthermore, based on electric navigation charts, a visual analytics system was built. Finally, three instances were illustrated and results demonstrated that it is conductive to the users in maritime department to make decisions depending on the knowledge they discovered from the visual analytics system.

Key words:  
vessel traffic in bridge waterway, visual analytics, automatic identification system (AIS) visualization, waterway transportation