社區犯罪基圖在汽車竊盜犯罪區位特性與預防之研究--以台北市士林區為例
- 發布日期:
- 最後更新日期:111-07-27
- 資料點閱次數:435
● 主管機關:內政部
● 執行機構:中央警察大學犯罪防治學系
● 研究期間:9607 ~ 9612
● 中文關鍵字:
汽車竊盜;犯罪預防;犯罪基圖;地理資訊系統
● 中文摘要:
● 英文摘要:
Auto-theft is one of the most frequent crimes in Taiwan nowadays and is closely related to geographical locations. This study is aimed to identify the hotspots of auto-theft in Beitou District, Taipei City in 2000 and 2004 and to determine the locational characteristics of these hotspots. The locations of auto-theft in Beitou District were converted into a point map by matching the addresses reported to the police. The auto-thefts were not randomly distributed, but concentrated in certain areas. Both auto-theft hotspots of Beitou District, Taipei City obtained by using kernel density and Getis-Ord G are concentrated on Shipai area,as well as areas around Beitou, Fuxinggang and Guandu. Especially, there was an increasing trend of auto-theft events in Guandu。Recently, in new Beitou sub district, the intensity also has been increased. Based on the spatial distribution, auto-thefts were highly concentrated in Shipai sub district, especially in Wenlin Li, Zhenhua Li, Fuxing Li, Yumin Li and Jianmin Li。Furthermore, the auto-theft rate was high inYide Li and Taoyuan Li in Guandu area。In addition, it was significant clustered in Datong Li and Zhongyang Li in old Beitou sub district。In the road sections, auto-thefts were highly concentrated on ChengDe Rd. Sec. 7, MingDe Rd., DaYe Rd., ZhongYang N. Rd. Sec. 3, ZhongYang N. Rd. Sec. 4 and WenLin N. Rd. Based on the findings of this research, we have some suggestions as follow: to reinforce the anti-auto-theft propaganda depending on the locational characteristics, to drive continuously “Keep Watch”, and to post the publicity material of anti-auto-theft in hotspots of auto-theft. For the purpose of complete monitoring, we should raise funding from the government and the private to set monitors in important intersections and hotspots. That will help deter, guard against and trace the auto-thieves. Furthermore, improving the illumination of parking lots and setting dynamic car license recognition system would strengthen the effect of anti-auto-theft. In addition, to understand the relationship between the locational characteristics and high-intensity auto-theft areas, it will be helpful to estimate crime rate reasonably from kernel density maps and contour distribution maps based on different types of crime in different time. The police can response crime phenomena effectively and allocate their resources in time. At last, as crime mapping and locational analysis advance, police officers should take some GIS education and apply GIS in their routine work. It will be supportive to collect, display and analyze the crime phenomena and trend in the police districts.
● 文章連結:
https://www.grb.gov.tw/search/planDetail?id=1446652
● 資料來源:
GRB政府研究資訊系統