Proceedings of the
35th European Safety and Reliability Conference (ESREL2025) and
the 33rd Society for Risk Analysis Europe Conference (SRA-E 2025)
15 – 19 June 2025, Stavanger, Norway
A 10-Year Analysis of the Global Maritime Accidents: From a Spatial and Temporal Perspective
1State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, China.
2Intelligent Transportation Systems Research Center, Wuhan University of Technology, China
3China Waterborne Transport Research Institute, China.
4COSCO Shipping Technology Co., Ltd., China.
ABSTRACT
Maritime accidents pose challenges to global shipping safety, affecting human lives and economic activities. Hotspot identification and analysis of maritime accidents is crucial for accident prevention, as it enables the identification of high-risk areas and supports targeted safety interventions. However, accurately pinpointing highrisk areas and implementing effective safety measures remain persistent challenges for the maritime industry worldwide. Based on the global ship accident data from 2013 to 2022, this study aims to employ advanced analytical techniques including Kernel Density Estimation (KDE) and Emerging Hot Spot Analysis (EHA) to identify maritime accident hotspots. The KDE method, which does not consider the temporal dimension, is used to explore the spatial distribution characteristics of ship accidents in two dimensions. In contrast, the GIS-based threedimensional spatiotemporal analysis method (i.e., emerging hot spot analysis) considers both spatial and temporal factors, allowing for a dynamic analysis of the spatiotemporal evolution of hot spots. The combination of KDE and EHA enables a comprehensive analysis of accident hotspots. The results reveal that the Europe, the English Channel, and the Strait of Malacca have consistently been accident hotspot regions. Additionally, the Mediterranean, the Singapore Strait, and the waters around China and Japan are areas where shipping accidents have continued to emerge as significant safety concerns. These regions have been identified as requiring particular attention regarding maritime safety management. Bases on EHA, this study also provides a detailed classification of hotspot patterns, enabling a comprehensive understanding of the spatio-temporal evolution of these accidents. Moreover, the study highlights the importance of implementing precise, region-specific safety interventions to proactively prevent accidents and enhance overall maritime safety.
Keywords: Kernel density estimation, Emerging hot spot analysis, Maritime safety, GIS.