街道夜間明亮度與竊案點位關係之初探

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。

關鍵字

犯罪熱區；空間自相關；街道照明與犯罪；犯罪預防；智慧城市

並列摘要

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.

並列關鍵字

Hotspot Analysis ； Spatial Autocorrelation ； Night Brightness and Crime Mapping ； Crime Prevention ； Smart City

參考文獻

Brantingham, P. L., Brantingham, P. J. J. S. o. C., & Prevention, C. (1999). A theoretical model of crime hot spot generation.

Google Scholar

Clarke, R. V. (1983). Situational crime prevention: Its theoretical basis and practical scope. Crime and justice, 4, 225-256.

Google Scholar

Clarke, R. V., & Criminology, B. J. (1980). Situational crime prevention: Theory and practice. 20, 136.

Google Scholar

Cohen, L. E., & Felson, M. J. A. s. r. (1979). Social change and crime rate trends: A routine activity approach. 588-608.

Google Scholar

Cornish, D., & Clarke, R. J. S. c. p. F. t. i. p. (1986). Situational prevention, displacement of crime and rational choice theory. 1-16.

Google Scholar

國際替代計量

街道夜間明亮度與竊案點位關係之初探

全文下載

主題瀏覽