Analysis of maritime piracy trends and patterns using spatial autocorrelation in Africa SCOPUS

Title
Analysis of maritime piracy trends and patterns using spatial autocorrelation in Africa
Author(s)
Whitney, Akhahenda; Kim, Hakchan; Son, Wooju; Lee, Jeongseok; Cho, Iksoon
KIOST Author(s)
Lee, Jeongseok(이정석)
Alternative Author(s)
이정석
Publication Year
2024-03
Abstract
Many studies have analyzed causation factors for piracy, but failed to quantitatively examine how piracy trends in regions have changed. The research aimed to establish the changing patterns of maritime piracy in Africa. The study utilized world piracy data from the National Geospatial Intelligence Agency, which was analyzed using spatial auto-correlation tools. Getis-Ord Gi* statistic identified piracy clusters and hot spot comparison tool compared the hot spot layers in East and West Africa. Autocorrelation analysis results suggest changing frequency of piracy incidents in the study areas before and after 2012. The mean Getis-Ord Gi* values for East Africa were 0.35946 and 0.07839 before and after 2012, illustrating agreater change. However, West Africa mean values were 0.60917 and 0.43408 pre and post 2012, suggesting minimal change. The comparison analysis results generated a smaller similarity value for East Africa (0.43350) and a larger index for West Africa (0.9867). West Africa recorded many incidents in the study period; hence, piracy intensity was almost similar. The study revealed high similarities in piracy events in West Africa, and low similarities in East Africa pre and post 2012. These have implications for understanding the changing dynamics of maritime piracy in Africa, and asserting spatial analysis.
ISSN
2572-5084
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/45435
DOI
10.1080/25725084.2024.2325274
Bibliographic Citation
Journal of International Maritime Safety, Environmental Affairs, and Shipping, v.8, no.1-2, 2024
Publisher
Taylor & Francis Group
Keywords
Maritime piracy; hot spot; spatial auto-correlation; getis-ord gi; spatial patterns
Type
Article
Language
English
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