文献类型：期刊文献

英文题名：A multi-method comprehensive analysis of the taxonomy-based risk assessment of fishing vessel safety in Guangdong Province

作者：Huang, Yingbang[1,2,3];Tang, Yu[2,4];Zhang, Tianyu[1,5,6];Zhou, LiLi[2,4]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang, Guangdong, Peoples R China;[2]Chinese Acad Fisheries Sci, South China Sea Fisheries Res Inst, Key Lab Marine Ranching, Minist Agr & Rural Affairs, Guangzhou, Peoples R China;[3]Sanya Trop Fisheries Res Inst, Hainan Engn Res Ctr Deep Sea Aquaculture & Proc, Sanya, Peoples R China;[4]Dalian Ocean Univ, Coll Nav & Naval Engn, Dalian, Liaoning, Peoples R China;[5]Guangdong Ocean Univ, Lab Coastal Ocean Variat & Disaster Predict, Zhanjiang, Peoples R China;[6]Minist Nat Resources, Key Lab Space Ocean Remote Sensing & Applicat, Beijing, Peoples R China

年份：2026

卷号：12

外文期刊名：FRONTIERS IN MARINE SCIENCE

收录：SCI-EXPANDED(收录号：WOS:001662968100001)、、Scopus(收录号：2-s2.0-105027886994)、WOS

基金：The author(s) declare that financial support was received for this work and/or its publication. This work was supported by: National Foreign Experts Program (No. S20240134); National Natural Science Foundation of China (No. 42476219, 42401111); Special Financial Funds of the Ministry of Agriculture and Rural Affairs 2025 (B050101, B050102); Special Financial Funds Project of Guangdong Province (2024-03024025).

语种：英文

外文关键词：geospatial analysis; maritime accident; Guangdong sea area; fishing vessel safety; risk assessment; Kernel Density Estimation (KDE); exploratory data analysis (EDA); International Maritime Organization (IMO) taxonomy

外文摘要：Introduction Fishing vessel safety is critical for the sustainable development of fisheries in Guangdong Province, China.Methods This study systematically assessed the safety status of fishing vessels based on data from 687 accidents between 2019 and 2023, using a multi-method framework that combines the International Maritime Organization (IMO) taxonomy, Kernel Density Estimation (KDE), grid-based accident location statistics, and Exploratory Data Analysis (EDA).Results Key findings reveal that "Collision" accidents accounted for the highest proportion (47.16%), representing the primary accident type; while "Mechanical Damage/Failure" incidents occurred less frequently (7.28%), 98% resulted in severe casualties, highlighting their high hazard potential. Significant differences in vessel length, tonnage, and power output were observed among fishing vessels of different materials (steel vs. fiberglass). Spatial analysis indicates that the coastal areas from Yangjiang and Maoming to Zhanjiang, along with the Pearl River Estuary, constitute extremely high-risk zones. Accident distribution exhibits pronounced spatiotemporal clustering, such as a peak in August and the highest risk occurring at 9:00 AM.Discussion Based on these findings, the study proposes targeted measures including strengthening technical prevention and precise supervision, establishing a dynamic risk-tiered control mechanism, and constructing a data-driven long-term management system. This study not only deepens systematic understanding of fishing vessel safety risks in Guangdong Province but also provides replicable empirical evidence and decision support for relevant fisheries safety authorities.