中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (2): 192-199.doi: 10.16265/j.cnki.issn1003-3033.2022.02.026

• 公共安全 • 上一篇    下一篇

以南疆为例的区域暴恐袭击风险评估

黄杰(), 张显峰   

  1. 北京大学 遥感与地理信息系统研究所,北京 100871
  • 收稿日期:2021-11-27 修回日期:2022-01-10 出版日期:2022-08-18 发布日期:2022-08-28
  • 作者简介:

    黄 杰 (1998—),男,江西都昌人,硕士研究生,主要研究方向为社会安全风险评估与应急管理、3S集成应用。E-mail:

    张显峰 教授

  • 基金资助:
    “十三五”新疆生产建设兵团重大专项(2017DB005)

Risk assessment of regional violent terrorist attacks in southern Xinjiang

HUANG Jie(), ZHANG Xianfeng   

  1. Institute of Remote Sensing and Geographic Information, Peking University, Beijing 100871, China
  • Received:2021-11-27 Revised:2022-01-10 Online:2022-08-18 Published:2022-08-28

摘要:

为探寻暴恐袭击高风险区域,推进公共安全精细化管理,以南疆地区为例,采用网格化社会经济数据、遥感数据和兴趣点 (POI) 数据等多源地理空间数据,从暴恐分子出现可能性、暴恐袭击目标选择偏好和暴恐袭击后果3个方面建立暴恐袭击风险评估指标体系,根据层次分析法(AHP)-Entropy、聚类分区等确定地理空间指标权重,最终得到南疆地区30″×30″(约1 km×1 km)细粒度的暴恐袭击风险的空间分布情况。结果表明:南疆地区的暴恐袭击高风险以上网格主要位于喀什、和田及阿克苏地区的部分市区和县城,与暴恐袭击历史事件的分布较一致,证明风险评估指标体系的合理性和可行性。

关键词: 南疆, 暴恐袭击, 风险评估, 兴趣点 (POI), 层次分析法(AHP), 熵权法(EWM)

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)