Risk assessment of regional violent terrorist attacks in southern Xinjiang

doi:10.16265/j.cnki.issn1003-3033.2022.02.026

Abstract

Abstract:

In order to examine high-risk areas of violent terrorist attacks and promote refined public security management, with southern Xinjiang, China as an example, gridded socio-economic data, remote sensing data, POI data, and other multi-source geospatial data were used to build a risk assessment indicator system of violent terrorist attacks from three aspects, namely occurrence probability of terrorists, preference of their target, and potential consequences of the attacks. Then, weights of geospatial indicators were determined according to AHP-Entropy method and cluster analysis method, and spatial distribution of attack risks on 30″ × 30″ (approximately 1 km×1 km) fine-granulated grids in southern Xinjiang was obtained. The results show that the high-risk grids of violent terrorist attacks in the area are mainly located in some cities and towns in Kashgar, Hotan and Aksu, which are consistent with distribution of historical attack events, therefore indicating the rationality and feasibility of proposed evaluation indicator model.

Key words: southern Xinjiang, violent terrorist attack, risk assessment, point of interest (POI), analytic hierarchy process (AHP), entropy weight method (EWM)

HUANG Jie, ZHANG Xianfeng. Risk assessment of regional violent terrorist attacks in southern Xinjiang[J]. China Safety Science Journal, 2022, 32(2): 192-199.

Figures/Tables 9

Fig.1

Tab.1

Tab.2

Fig.2

Fig.3

Tab.3

Weights for indices of terrorist occurrence probability

目标层	一级指标	二级指标	熵权 $u j$	AHP权重 $w j$	综合权重 $v j$
暴恐分子出现可能性	自然条件	降水	0.054	0.056	0.075
		海拔高度	0.008	0.052	0.028
		NDVI	0.004	0.054	0.021
	社会背景	人口密度	0.517	0.145	0.279
		汉族人口比例	0.010	0.122	0.047
		GDP	0.329	0.127	0.374
		夜间灯光	0.073	0.114	0.124
	地理环境	到最近城镇的最短通行时间	0.002	0.157	0.023
	地理环境	到边境线的最短通行时间	0.003	0.173	0.029

Tab.3

Tab.4

Tab.5

Weights for indices of terrorist attack consequence

目标层	一级指标	二级指标	熵权 $u j$	AHP权重 $w j$	综合权重 $v j$
暴恐袭击后果	经济损失	GDP	0.323	0.163	0.234
	经济损失	建成区面积	0.263	0.297	0.285
	人员伤亡	人口密度	0.415	0.540	0.481

Tab.5

Fig.4

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目标层	一级指标	二级指标
暴恐分子出现可能性	自然条件	降水(+)
		海拔高度(-)
		NDVI (-)
	社会背景	人口密度(+)
		汉族人口比例(-)
		GDP (+)
		夜间灯光(+)
	地理位置	到最近城镇的最短通行时间(-)
	地理位置	到边境线的最短通行时间(-)

目标层	指标层	权重w_j
暴恐分子目标选择偏好	交通设施	0.322
	景点住宿	0.106
	教育医疗	0.054
	企业公司	0.071
	生活娱乐	0.175
	政府机构	0.272