Time-Series Analysis of Ship Movements Using Community Detection and Functional Data Analysis across the East Coast of the Republic of Korea

Abstract

Kim, G.; Jeong, M.-H.; Jeon, S.-B., and Khan, M.S., 2023. Time-series analysis of ship movements using community detection and functional data analysis across the east coast of the Republic of Korea. Journal of Coastal Research, 39(2), 360–365. Charlotte (North Carolina), ISSN 0749-0208. Because of the recent climate change caused by air pollution in ports, global interest in marine spatial planning (MSP) has increased to achieve cost-effective navigation, economic development goals, logistics, and energy transportation. Accordingly, research on ship traffic, the main cause of air pollution in ports, is attracting attention. This study aims to investigate the temporal characteristics of the port network on the east coast of the Republic of Korea using the automatic identification system data set. This study used the Louvain model, a community detection technique for complex networks, and functional data analysis (FDA). The results of the Louvain model showed that the port network of the Republic of Korea has a hub-and-spoke structure in which ports that are close to each other are regionally clustered around the main ports in the community. The FDA results showed seasonal changes in port arrival volume and detection of abnormal ports in Korea's east-coast ports. The results of this study are expected to provide a baseline for policy makers to establish an effective MSP for port management, cost-effective route development, and prediction of the number of operations.