Spatial patterns and characteristics of global maritime accidents

Yang Zhang, Xukai Sun, Jihong Chen and Cheng Cheng

Reliability Engineering and System Safety, 2021, vol. 206, issue C

Abstract: Maritime safety has become one of the top concerns of the global maritime sector in recent years. This paper explores the spatial patterns and characteristics of maritime accidents on a global scale. Maritime accident data dating from 2003 to 2018 from the Marine Casualties and Incidents (MCI) module of the Global Integrated Shipping Information System (GISIS) was collected and manipulated and descriptive analyses were conducted subsequently to obtain the overall profile of global maritime accidents. Geospatial techniques of Kernel Density Estimation (KDE) and K-means clustering method were introduced and parameters specifically used in this study were identified. These geospatial techniques were utilized to a) create a number of KDE maps of global maritime accidents, and b) subdivide these accidents into six classes and profile characteristics of maritime accidents within each class. Maritime accidents are more likely to occur around the United Kingdom, Denmark, Singapore, and Shanghai of China. This may be due to the large cargo volume, the high density of routes, the poor geographical conditions of the sea area and the poor climate conditions in these areas. Distributions of maritime accidents by time, initial event, and ship type are found to be diverse in different accident classes.

Keywords: Maritime accident; GIS; Spatial pattern; KDE; K-means clustering analysis (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:206:y:2021:i:c:s0951832020308061

DOI: 10.1016/j.ress.2020.107310

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