臺灣博碩士論文加值系統

觀念上，車輛竊盜犯罪行爲與車輛所處的環境條件有著高度的關連性。為了瞭解車輛竊盜案件與環境條件間的關係，本研究應用Kernel Density Estimation (KDE)方法，結合GIS的空間分析工具，以進行車輛竊盜犯罪熱點之識定，再藉由Crime Prevention Through Environment Design (CPTED)的指導，以提出車輛竊盜所處環境在環境設計上可能的改善方式。研究中首先回顧車輛竊盜犯罪與環境設計間的關係，以擬定本研究的架構。藉由台中市西屯區警察局所提供的車輛竊案原始數據，將其與地理座標位置連結，以做為KDE分析的輸入資料。透過GIS空間分析工具的結合，將前述實際的車輛竊盜資料轉換為犯罪熱點資料並展示在地圖上，再透過空間統計模型，以分析出車輛竊盜犯罪高密度的位置。

透過KDE 的分析並發現5個車輛竊盜犯罪高密度的位置，應用這5個位置並選定“視線”環境檢查清單來審查其環境。將事發時間分成2時段為上午9:00至下午8:59 為(日間)及下午9:00到上午8:59為（夜間）來觀察其研究領域。在視線不佳，路燈光度不足，監視器不足，鋁板圍牆，高草和混凝土牆等領域和汽車之間有個隱藏空間的情況下車輛可隨時被偷盜。

憑藉熱點空間分析所取得的成果，在預防車輛竊盜犯罪的戰略上應徹底觀察並檢查熱點中的問題位置並實施CPTED環境檢查清單。應用KDE和CPTED不只能更了解及簡化車輛竊盜犯罪之研究，並使其更可靠的改善我們的生活品質。此成果的用途可提供給預防車輛竊盜的政策制定者和警察部門為參考資料。

In concepts, vehicle crimes are highly related to certain characteristics of the built environment of parking environment. In order to understand the relationship between vehicle crimes and parking environment conditions, an analysis tool of GIS was implemented in this research by integrating the kernel density estimation (KDE) method and the improvement for parking environment design through the possibility methods of Crime Prevention Through Environment Design (CPTED). Firstly, a research framework dealing with the relationship between vehicle crime and environment design was established through the literature review. Then, the raw data provided by Taichung City Police Bureau of Xitun District(台中市西屯區警察局)were converted into geographical data and imported for KDE analysis. Through the combination of GIS spatial analysis tool and statistical spatial model, it could identify and provide valuable spatial information of high density vehicle crime hotspots location which plotted on the map.

There are 5 places where high vehicle crime of hotspots density had been found through the KDE analysis. Apply these 5 places into the selected checklist guidelines of “Sight Lines” to review its environments. Divide the incidence time into 2 parts to observe the research areas from 9:00AM to 8:59PM (Day time) and (Night time) from 9:00PM to 8:59AM. Vehicles can be stolen at anytime in the areas of poor sight lines, inadequate of street lights and poor light lit, inadequate of CCTV, a hiding gaps between car and aluminum plates’ fences, tall grasses and concrete wall.

Through the result of hotspot spatial analysis, the strategies of crime prevention should be re-observed and inspect thoroughly in hotspots problematic area with implementing CPTED checklists guidelines. Applying KDE and CPTED will not only make easier to the vehicle crime research and also make it more reliable for improving our living standards through a better understanding of spatial vehicle crime. The result can be a useful reference for policy makers and police department for vehicle crime prevention.

Chapter 1: Introduction
1.1. Background and Motivations
1.2. Research Objectives
1.3. Structure of the Thesis

Chapter 2: Literature Review
2.1. The Notions of Vehicle Theft
2.2. Theory of Environmental Criminology
2.3. Theory of Crime Occurrence Potentiality

Chapter 3: Analytical Approach and Frameworks
3.1. Research Design
3.2. Research Methodology
3.3. Limitation of Research

Chapter 4: Empirical Studies
4.1. Observation of Research Area
4.2. Data Manipulation
4.3. Analysis of Crime Spatial
4.4. Analysis of Crime Time Slot
4.5. Observation of Low Hotspots Density Areas

Chapter 5: Conclusions and Remarks
5.1. Conclusions
5.2. Remarks and Future Works

References

1.賴致瑜, 張平吾, 張康聰, (2005),台北市住宅竊盜犯罪熱點及其社經人文環境分析之研究,中央警察大學犯罪防治學報第6 期,頁29-54,桃園:中央警察大學犯罪防治研究所.
2.Brimicombe, A. (2004), On being more robust about ’hot spots’, pp. 234-240, In Proceedings of The Seventh Annual Crime Mapping Research Conference, Boston, Massachusetts, USA.
3.Brantingham, P.L. and Brantingham P.J. (1981), Environmental Criminology, Beverly Hills, CA: Sage Publications, 27-53.
4.Brantingham & Brantingham (1991) Environmental Criminology. (Prospect Hills, Illinois: Waveland Press, Inc.
5.Clarke and Harris, R.V. (1992). Situational Crime Prevention: Successful Case Studies. Albany, NY: Harrow and Heston.
6.Cohen and Felson (1979). "Social Change and Crime Rate Trends: A Routine Activity Approach." American Sociological Review 44:588-608.
7.Chainey, S. and Ratcliffe, J. (2005), GIS and Crime Mapping, John Wiley and Sons, UK.
8.Derek J. Paulsen (2003). Assistant Professor, Department of Criminal Justice, Eastern Kentucky University. USA.
9.Dr. R. Sahu & Peeyush Srivastava (2004). “Effective Crime Control using GIS”, Indian Institute of Information Technology & Management, Gwalior.
10.Fleming, Z., Brantingham, P., & Brantingham, P. (1994). Exploring auto theft in British Columbia. In R.V. Clarke (ed.), Crime Prevention Studies, Vol 3, pp. 47-90. New York: Criminal Justice Press.
11.General Guidelines For Designing Safer Communities (2000), Crime Prevention Through Environmental Design, City of Virginia Beach, Municipal Center, Virginia Beach.
12.Gant, F., & Grabosky, P. (2001). The stolen vehicle parts market. Trends and Issues in Crime and Criminal Justice (no. 215). Canberra: Australian Institute of Criminology.
13.Jock Young, (1999), The Exclusive Society, Ch.5. London: Macmillan.
14.John Eck (1995). "A General Model of the Geography of Illicit Retail Marketplaces." In: J.E. Eck and D. Weisburd (eds.), Crime and Place. Crime Prevention Studies, vol. 4. Monsey, NY: Criminal Justice Press.
15.Lab P. S. (2000), Crime Prevention: Approaches, Practices and Evaluations, Anderson Publishing Co., Cincinnati,OH.
16.McLafferty, S., Williamson, D. and McGuire, P. G. (2000), Identifying crime hot spots using kernel smoothing, pp. 77–85, In V. Goldsmith; P. G. McGuire; J. H. Mollenkopf, & T. A. Ross (Eds.), Analyzing crime patterns: Frontiers of practice. Thousand Oaks, CA: Sage.
17.Miethe, T.D. (2010), Criminology Lecture Series, NV: CJ Research, Las Vegas.
18.Marcus Felson (1998). Crime and Everyday Life, Second edition. Thousand Oaks, CA: Pine Forge Press.
19.National Crime Prevention Council (2003), Crime Prevention Through Environmental Design Guidebook. Singapore
20.Paul and Patricia Brantingham, (1984). Patterns in Crime. New York, NY: Macmillan.
21.Ractiffe, J.H. and McCullagh, M.J. (1999), “Hotbeds of crime and the search for spatial accuracy”, Geographical Systems, 1, 385-398.
22.Schmalleger F (1996). Criminology Today. New Jersey: Prentice Hall.
23.Sabel, C., Kingham, S., Nicholsan, A. and Bartie, P. (2005), Road Traffic Accident Simulation Modelling - A Kernel Estimation Approach, pp. 67-75, In The 17th Annual Colloquium of the Spatial Information Research Centre University of Otago, Dunedin, New Zealand.
24.Silverman, B.W. (1986), Density Estimation for Statistics and Data Analysis, Chapman and Hall: New York.
25.Timothy D. Crowe (1991), National Crime Prevention Institute (University of Louisville) Criminologist & CPTED Practitioner.
26.Verma & Lodha: (2002). "A Typological Representation of the Criminal Event." Western Criminology Review 3(2).