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GIS-based analysis on the spatial patterns of global maritime accidents

Huanxin Wang, Zhengjiang Liu, Zhengjiang Liu, Zhichen Liu, Zhichen Liu, Xinjian Wang, Jin Wang

2022Ocean Engineering69 citationsDOIOpen Access PDF

Abstract

Based on the global maritime accident data from 2010 to 2019, density analysis and clustering analysis have been used to analyse the spatial patterns of maritime accidents in terms of accident frequency and severity. The North Sea, the Baltic Sea and the Mediterranean Sea form low severity accident clustering. More than 60% accidents are found within the sea areas less than 30 nm to the coastline. As to the spatial characteristics of maritime accident severity, the coastal waters surrounding China, Japan, South Korea, Vietnam and the Philippines, the Singapore-Malacca Strait and the Bay of Biscay form high severity accident clustering. The North Sea, the Baltic Sea and the Mediterranean Sea form low severity accident clustering in the clustering analysis although they have medium and high densities of accident severity in the density analysis. Almost 60% of serious accidents and very serious accidents are found within 30 nm to the coastline. The comparison of the results of density analysis and clustering analysis indicate that the latter can provide more abundant spatial characteristic information, while the former is superior in terms of simplicity and computational efficiency. This study provides useful information to assist the relevant maritime authorities in improving maritime traffic management.

Topics & Concepts

Cluster analysisMediterranean seaBaltic seaSpatial analysisGeographyChinaMediterranean climateGeographic information systemEnvironmental scienceCartographyOceanographyComputer scienceGeologyRemote sensingArchaeologyMachine learningMaritime Navigation and SafetyMaritime Ports and LogisticsMaritime Security and History
GIS-based analysis on the spatial patterns of global maritime accidents | Litcius