Shifting landscape of terrorism: A 50‐year spatiotemporal analysis DOI
Shupeng Lyu, Qian Chen, Ching‐Hung Lee

et al.

Risk Analysis, Journal Year: 2025, Volume and Issue: unknown

Published: March 30, 2025

Abstract This study aims to analyze the spatiotemporal evolutionary characteristics of global terrorism from 1970 2020, providing a comprehensive understanding its dynamics and patterns. The research seeks fill gaps in existing literature by integrating geographic perspectives methods enhance terrorism's spatial temporal dimensions. employs multi‐methodological approach, combining Mann–Kendall trend test, autocorrelation analysis, kernel density estimation, standard deviational ellipse. These are applied data 176 countries, covering 171,327 terrorist incidents recorded Global Terrorism Database (GTD) 2020. Pertinent findings as follows. Temporally, risk has evolved significantly over past five decades involves four distinct stages, i.e., emerging stage (1970–1991), descending (1992–2000), rampant (2001–2014), attenuating (2015–2020). Meanwhile, 117 countries show an increasing trend, 56 decreasing risk. Spatially, distribution is characterized clustering aggregation, with constant shift gravity center dominant direction. In addition, hotspots predominantly presented “two major core circles multiple sub‐centers.”

Language: Английский

Skip or not: Hybrid machine learning for decision support in strategic port-skipping behavior to enhance liner shipping reliability DOI

Xingcan Fan,

Jing Lyu, Lingye Zhang

et al.

Ocean Engineering, Journal Year: 2025, Volume and Issue: 324, P. 120730 - 120730

Published: Feb. 22, 2025

Language: Английский

Citations

0
Shifting landscape of terrorism: A 50‐year spatiotemporal analysis DOI
Shupeng Lyu, Qian Chen, Ching‐Hung Lee

et al.

Risk Analysis, Journal Year: 2025, Volume and Issue: unknown

Published: March 30, 2025

Abstract This study aims to analyze the spatiotemporal evolutionary characteristics of global terrorism from 1970 2020, providing a comprehensive understanding its dynamics and patterns. The research seeks fill gaps in existing literature by integrating geographic perspectives methods enhance terrorism's spatial temporal dimensions. employs multi‐methodological approach, combining Mann–Kendall trend test, autocorrelation analysis, kernel density estimation, standard deviational ellipse. These are applied data 176 countries, covering 171,327 terrorist incidents recorded Global Terrorism Database (GTD) 2020. Pertinent findings as follows. Temporally, risk has evolved significantly over past five decades involves four distinct stages, i.e., emerging stage (1970–1991), descending (1992–2000), rampant (2001–2014), attenuating (2015–2020). Meanwhile, 117 countries show an increasing trend, 56 decreasing risk. Spatially, distribution is characterized clustering aggregation, with constant shift gravity center dominant direction. In addition, hotspots predominantly presented “two major core circles multiple sub‐centers.”

Language: Английский

Citations

0