隨著都市地區人口成長，為了都市永續發展「智慧城市」的概念越趨重要。在智慧城市的許多面向中，都市治安往往是評估一個都市治理成效的重要指標。根據聯合國安全城市議程（UN-Habitat’s Safer Cities Programme），都市治安應包含降低犯罪率、提供居民健康的環境與醫療資源、以及加強緊急事件應變能力。其中在打擊犯罪率的部分，智慧城市強調防患未然，藉由統計犯罪行為聚集點來預測潛在犯罪熱區、搭配對特定地區加強巡邏等警政資源的統合預防犯罪等方式來提升都市安全。
　從情境預防理論來看，犯罪往往起因於有利於犯罪的條件，而街道照明程度由於會影響可視性以及當地居民的生活習慣，例如行走路線或夜間活動時間，增強夜間照明從理論上也能同時增加環境監視資源，使潛在犯罪者不敢輕舉妄動。然而不同燈光照明強度與不同地區對燈光的反應不盡相同，本研究藉由比對臺北市竊案與夜間街道明亮度的空間分布，來探討犯罪分布是否會受不同街道照明強度影響。透過對104~107年臺北市住宅、汽車與自行車的竊案發生點位以及影響街道明亮的重要地標（Point of Interest, POI）資料進行空間自相關分析，本研究分別繪製了臺北市竊案熱區圖及夜間街道明亮度分布圖。成果顯示，若將燈光密集度由弱到強劃分為1至10級，在燈光密集度為等級3時，竊案發生次數最高。這可能與有燈光但燈光昏黃的環境可增加潛在犯罪者鎖定標的物或觀察作案條件，形成有利的犯罪環境有關。

Urban security is often considered as an evaluation criteria of urban governance. According to UN-Habitat Safer Cities Programme, there are three key considerations in urban security: low crime rates, safe living environment and sufficient medical resources, and effective responses toward emergencies. With the core values of smart city and eager of enhanced city safety, Taipei city government has launched a program for the monitoring of burglary, bicycle and vehicle theft in Taipei since 2015. To prevent the increase of crime events, it is essential to understand spatial patterns of crime hotspots and take effective actions. Research has found the brightness of street lights plays a positive role in the reduction of crime rate. Bright street lights at night make pedestrians feel safe and comfortable, and raise the risks of exposures for criminals. In some research, however, dimly street lighting formed a unique environment for the happening of potential crimes, for example, easy to lock on targets. As a result, it is essential to explore positive influences of brighter street lights on crime. It is equally important to figure out how various degrees of brightness affect the frequency of crimes. By spatial autocorrelation, this study conducts hotspot analysis of location for residential burglary, bicycle and vehicle theft in Taipei since 2015 to 2018. The brightness of street lights is categorized to ten levels and drawn on a map overlaid with point of interest （POIs） which affect street brightness at night in Taipei. The results show that the number of burglary and theft events raise significantly when the brightness of street lights is category 3. This study reflects that the dimly street lighting provides a suitable environment for potential crimes, and helps the government to strategically build up environmental surveillance systems based on the spatial patterns of brightness and other related features for a sustainable and smarter city.

Brantingham, P. L., Brantingham, P. J. J. S. o. C., & Prevention, C. (1999). A theoretical model of crime hot spot generation.
Clarke, R. V. (1983). Situational crime prevention: Its theoretical basis and practical scope. Crime and justice, 4, 225-256.
Clarke, R. V., & Criminology, B. J. (1980). Situational crime prevention: Theory and practice. 20, 136.
Cohen, L. E., & Felson, M. J. A. s. r. (1979). Social change and crime rate trends: A routine activity approach. 588-608.
Cornish, D., & Clarke, R. J. S. c. p. F. t. i. p. (1986). Situational prevention, displacement of crime and rational choice theory. 1-16.
CS. (2018, 2018). What Smart Cities are Doing to Increase Our Safety. Campus Safety
Doxiadis, C. A. J. E. (1962). ekistics and Regional Science. 14(84), 193-200.
ESRI. (2019). How Hot Spot Analysis (Getis-Ord Gi*) works. Retrieved from https://pro.arcgis.com/en/pro-app/tool-reference/spatial-statistics/h-how-hot-spot-analysis-getis-ord-gi-spatial-stati.htm
Farrington, D. P., & Welsh, B. C. (2002). Effects of improved street lighting on crime: a systematic review: Citeseer.
Fedorov, O. V., Kosobokov, M. D., Levin, V. V., Struchkova, M. I., & Dilman, A. D. (2015). Halogenative difluorohomologation of ketones. The Journal of organic chemistry, 80(11), 5870-5876.
Felson, M., Clarke, R. V. J. R., Development, & Office, S. D. L. H. (1998). Opportunity Makes the Thief. Police Research Series, Paper 98. Policing and Reducing Crime Unit.
IBM. (2008). 智慧地球: 下一代領導人議程. Retrieved from https://www.ibm.com/ibm/history/ibm100/us/en/icons/smarterplanet/
IBM. (2019). Smart City. Retrieved from http://www-07.ibm.com/tw/dp-cs/smartercity/solutions.html
Jacobs, J. (1961). The Death and Life of Great American Cities.
Pease, K. (1999). A review of street lighting evaluations: Crime reduction effects. Crime prevention studies, 10(1), 47-76.
Sherman, L. W., & Weisburd, D. J. J. q. (1995). General deterrent effects of police patrol in crime “hot spots”: A randomized, controlled trial. 12(4), 625-648.
Steinbach, R., Perkins, C., Tompson, L., Johnson, S., Armstrong, B., Green, J., . . . Edwards. (2015). The effect of reduced street lighting on road casualties and crime in England and Wales: controlled interrupted time series analysis. J Epidemiol Community Health, 69(11), 1118-1124.
Thessin, R., & Beatty, J. K. (2002). Bright lights, big problems. Sky and Telescope, 104(6), 32.
UN-Habitat. (1996). Safer Cities Programme. Retrieved from https://unhabitat.org/urban-initiatives/initiatives-programmes/safer-cities/
Welsh, B. C., & Farrington, D. P. (2008). Effects of improved street lighting on crime. Campbell systematic reviews, 4(1), 1-51.
內政部警政署刑事警察局（2019）。犯罪預防寶典。檢自https://www.cib.gov.tw/Crime
何明洲（2004）臺灣地區汽車被竊環境因素之實證研究。中央警察大學警學叢刊。
吳斯茜、黃家珍（2017)。城市治理與治安衡量指標之探討。中央警察大學警察行政管理學報。
李孟澤（2007）。情境犯罪預防之原理與實務。檢自 http://skyocean888.blogspot.com/2014/10/blog-post_29.html
李宗霖（2013）。從自然監視的環境設計手法探討活動混合對竊盜犯罪的影響-以台北市北投區為例。
李瑞陽、陳勝義（2010）。臺中市搶奪犯罪熱點與犯罪區位之空間分析。地理研究。
周天穎、賴玉真、杜雅齡（2015）。國際智慧城市發展指標與評比機制。國土及公共治理季刊，3(2)，8-18.
孟维德（2005）。警察與犯罪控制。五南圖書出版股份有限公司。
林美君、蘇明道、溫在弘（2005）。空間點型態分析－臺北市照護分析。2005年台灣地理資訊學會年會暨學術研討會。
林書玄（2018）。住宅竊盜犯罪特性及被害風險評估之研究─以臺北市士林區為例。銘傳大學。
林欽榮（2017）。城市治理與智慧城市產業驅動臺北策略。國土及公共治理季刊，5(4)，
82-91。
邱錦堂（2013）。機車竊盜犯罪區位特性之研究。
胡立諄、賴進貴（2006）。臺灣女性癌症的空間分析。臺灣地理資訊學刊，39-55。
溫在弘、劉擇昌、林民浩（2010）。犯罪地圖繪製與熱區分析方法及其應用。地理研究。
葉晉嘉（2010）。各國創意城市指標的比較性研究。城市發展(9)，111-144。
臺北市政府資訊局（2011）。Data Taipei臺北市政府資料開放平台。檢自https://data.taipei/#/
臺北市政府資訊局（2015）。「治安透明 市民安心」臺北市住宅、汽車及自行車竊盜案資料開放。檢自 http://bit.ly/2ORC1TX
臺北市政府警察局（2018）。警務統計年報。臺北市政府警察局。檢自http://bit.ly/2SIYmEa
賴銘昌（2006）。空間型構與汽車竊盜之關聯性研究－以台灣某都市為例。逢甲大學。
謝文彥、廖有祿（2007）。社區犯罪基圖在機車竊盜區位犯罪特性之研究。檢自 https://goo.gl/yaGp6a