中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地理科学与资源研究所
  3. 中国科学院地理科学与资源研究所
  4. 自然资源与环境安全研究部
  5. 外文论文
Simulating Spatio-Temporal Patterns of Terrorism Incidents on the Indochina Peninsula with GIS and the Random Forest Method

文献类型：期刊论文

作者Hao, Mengmeng2,3; Jiang, Dong1,2,3; Ding, Fangyu2,3; Fu, Jingying2,3; Chen, Shuai2,3
刊名ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
出版日期2019-03-07
卷号8期号:3页码:19
关键词terrorism incidents spatio-temporal patterns Geo-information system RF Algorithm Indochina Peninsula
ISSN号2220-9964
DOI10.3390/ijgi8030133
通讯作者Jiang, Dong(jiangd@igsnrr.ac.cn)
英文摘要In recent years, various types of terrorist attacks have occurred which have caused worldwide catastrophes. The ability to proactively detect and even predict a potential terrorist risk is critically important for government agencies to react in a timely manner. In this study, a method of geospatial statistics was used to analyse the spatio-temporal evolution of terrorist attacks on the Indochina Peninsula. The machine learning random forest (RF) method was adopted to predict the potential risk of terrorist attacks on the Indochina Peninsula on a spatial scale with 15 driving factors. The RF model performed well with AUC values of 0.839 [95% confidence interval of 0.833-0.844]. The map of the potential distribution of terrorist attack risk was obtained with a 0.05x0.05-degree (approximately 5x5 km) resolution. The results indicate that Thailand is the most dangerous area for terrorist attacks, especially southern Thailand, Bangkok and its surrounding cities. Middle Cambodia and the northern and southern parts of Myanmar are also high-risk areas. Other areas are relatively low risk. This study provides the hotspots for terrorist attacks on a more fine-grained geographical unit. Meanwhile, it shows that machine learning algorithms (e.g., RF) combined with GIS have great potential for simulating the risk of terrorist attacks.
WOS关键词ARMED-CONFLICT ; CLIMATE-CHANGE ; CIVIL CONFLICT ; ENVIRONMENTAL DEGRADATION ; POPULATION PRESSURE ; TIME-SERIES ; RESPONSES ; SCARCITY ; ATTACKS
资助项目Chinese Academy of Sciences[KGFZD-135-17-009] ; Chinese Academy of Sciences[ZDRW-ZS-2016-6]
WOS研究方向Physical Geography ; Remote Sensing
语种英语
WOS记录号WOS:000464226000002
出版者MDPI
资助机构Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/48207]  
专题资源利用与环境修复重点实验室_外文论文
通讯作者Jiang, Dong
作者单位1.Minist Land & Resources, Key Lab Carrying Capac Assessment Resource & Envi, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resource & Environm, 19 Yuquan Rd, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Hao, Mengmeng,Jiang, Dong,Ding, Fangyu,et al. Simulating Spatio-Temporal Patterns of Terrorism Incidents on the Indochina Peninsula with GIS and the Random Forest Method[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(3):19.
APA Hao, Mengmeng,Jiang, Dong,Ding, Fangyu,Fu, Jingying,&Chen, Shuai.(2019).Simulating Spatio-Temporal Patterns of Terrorism Incidents on the Indochina Peninsula with GIS and the Random Forest Method.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(3),19.
MLA Hao, Mengmeng,et al."Simulating Spatio-Temporal Patterns of Terrorism Incidents on the Indochina Peninsula with GIS and the Random Forest Method".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.3(2019):19.

入库方式： OAI收割

来源：地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。