open access publication

Article, 2024

PiracyAnalyzer: Spatial temporal patterns analysis of global piracy incidents

Reliability Engineering & System Safety, ISSN 1879-0836, 0951-8320, Volume 243, Page 109877, 10.1016/j.ress.2023.109877

Contributors

Liang, Maohan 0000-0001-7470-3313 [1] [2] Li, Huanhuan 0000-0002-4293-4763 [3] Liu, Ryan Wen 0000-0002-1591-5583 [2] Lam, Jasmine Siu Lee 0000-0001-7920-2665 (Corresponding author) [4] Yang, Zaili L 0000-0003-1385-493X [3]

Affiliations

  1. [1] National University of Singapore
  2. [NORA names: Singapore; Asia, South];
  3. [2] Wuhan University of Technology
  4. [NORA names: China; Asia, East];
  5. [3] Liverpool John Moores University
  6. [NORA names: United Kingdom; Europe, Non-EU; OECD];
  7. [4] Technical University of Denmark
  8. [NORA names: DTU Technical University of Denmark; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Maritime piracy incidents present significant threats to maritime security, resulting in material damages and jeopardizing the safety of crews. Despite the scope of the issue, existing research has not adequately explored the diverse risks and theoretical implications involved. To fill that gap, this paper aims to develop a comprehensive framework for analyzing global piracy incidents. The framework assesses risk levels and identifies patterns from spatial, temporal, and spatio-temporal dimensions, which facilitates the development of informed anti-piracy policy decisions. Firstly, the paper introduces a novel risk assessment mechanism for piracy incidents and constructs a dataset encompassing 3,716 recorded incidents from 2010 to 2021. Secondly, this study has developed a visualization and analysis framework capable of examining piracy incidents through the identification of clusters, outliers, and hot spots. Thirdly, a number of experiments are conducted on the constructed dataset to scrutinize current spatial-temporal patterns of piracy accidents. In experiments, we analyze the current trends in piracy incidents on temporal, spatial, and spatio-temporal dimensions to provide a detailed examination of piracy incidents. The paper contributes new understandings of piracy distribution and patterns, thereby enhancing the effectiveness of anti-piracy measures.

Keywords

accidents, analysis, analysis framework, anti-piracy measures, assessment mechanism, clusters, comprehensive framework, construction, crew, damage, dataset, decision, development, dimensions, distribution, diverse risks, effect, examination, experiments, framework, gap, hot spots, identification, identification of clusters, implications, incidence, issues, levels, maritime security, material damage, materials, measurements, mechanism, outliers, pattern analysis, patterns, piracy, piracy incidents, policy decisions, research, risk, risk assessment mechanism, risk level, safety, safety of crew, security, significant threats, spatial-temporal pattern analysis, spatial-temporal patterns, spatio-temporal dimensions, spots, study, temporal pattern analysis, theoretical implications, threat, trends, visualization

Funders

  • China Scholarship Council
  • European Research Council

Data Provider: Digital Science