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-司法保護與刑事政策研究資料庫

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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： 111-07-27
最後更新日期：111-07-27
資料點閱次數：431

● 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：

一、研究緣起「竊盜」是國內現今發生頻率最高的犯罪，除了帶給民眾財物的損失外，還會令被害者感到私領域被侵犯，產生不安全感，造成民眾對社會治安負面觀感。「汽車竊盜」對民眾的安全感與對地區治安的觀感侵害極大，本研究針對台北市北投區汽車竊盜犯罪情況進行分析，運用警政署刑事警察局的犯罪發生地址資料進行地理編碼，建立汽車竊盜犯罪點分佈圖（crime event maps）。二、研究方法及過程本研究藉由地理資訊系統(GIS)的空間分析(spatial analysis)方法，找出犯罪高度集中區，即犯罪熱點(hotspots)之所在，可協助警方掌握台北市北投區汽車竊盜犯罪的空間分佈型態。並透過不同年度的汽車竊盜犯罪空間分佈型態進行視覺化處理，從空間與時間面向，歸納出汽車竊盜犯罪空間的變遷趨勢。除此之外，本研究加入2000年戶口及住宅普查資料與2001年工商普查資料進行空間迴歸分析，探討汽車竊盜犯罪熱點的區域特性，找出可能影響汽車竊盜犯罪的人文社經環境因子，提供汽車竊盜犯罪防治工作之決策與規劃參考。三、重要發現本研究分析2000～2004區年北投區汽車竊盜資料，研究發現北投區汽車竊盜的犯罪地點確實呈現聚集現象，由核密度分佈圖，可以清楚地判別汽車竊盜的變遷趨勢。北投汽車竊盜空間分佈始終高度集中在石牌地區，在北投、復興崗、關渡一帶亦有犯罪熱點凸顯，尤其關渡附近地區的犯罪熱點有增強的趨勢。近年來，新北投次分區的犯罪集中程度亦有提高。依據空間分佈觀點，2000～2004年北投區汽車竊盜案件分佈高度集中在石牌次分區，尤其是文林里，及其周圍的振華里、福興里、裕民里、建民里。關渡地區的一德里與桃源里亦呈現高犯罪率。而舊北投次分區的大同里與中央里的犯罪率亦頗為顯著。在路段方面，研究發現，承德路七段、明德路、大業路、中央北路三段、中央北路四段及文林北路為主要發生地點。四、主要建議事項根據研究發現，本研究建議如下：各里依其被害特性加強汽車防竊宣導，持續推動守望相助，對竊盜犯罪發生頻率較高地區或路段，印製海報張貼提醒民眾防竊。為達全面監控目標，建議由政府編列預算或由民間力量集資捐助在重要路口或易遭竊地區、路段設置監視器，可發揮威嚇、防範及蒐證作用。推動自動感應器照明設備，增加照明度。收費停車場出入口，建構先進車號辨識系統，管制車輛進出，防止被竊。另外，建議未來可針對不同犯罪類型，繪製不同時間的核密度及等高線犯罪分佈圖，分析各類型犯罪熱點隨時間變化的趨勢，進行更合理的推估，以充分掌握犯罪熱區與區位特性間的相關性，以協助警察提出有效勤務的因應作為。警察機關應加強GIS系統基礎教育，以普遍運用GIS系統，統計及分析各警勤區之犯罪現象及其變遷趨勢，作為改進勤務規劃之依據。

● 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