open access publication

Article, 2024

PiracyAnalyzer: Spatial temporal patterns analysis of global piracy incidents

Reliability Engineering and System Safety, ISSN 0951-8320, Volume 243, 10.1016/j.ress.2023.109877

Contributors

Liang M. 0000-0001-7470-3313 [1] [2] Li H. 0000-0002-4293-4763 [3] Liu R.W. 0000-0002-1591-5583 [2] Lam J.S.L. 0000-0001-7920-2665 (Corresponding author) [4] Yang Z. 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

Data visualization, Hot spots, Maritime security, Piracy incidents, Spatial-temporal patterns

Funders

  • China Scholarship Council
  • European Research Council

Data Provider: Elsevier