空間大數據分析於提升警務執法效能之應用與他山之石

The Application and Reference Cases on Spatial Big Data Analysis in Improving Effectiveness of Police Law Enforcement

本文以文獻探討方式首先對於運用空間大數據分析提升警務執法效能工作之背景知識加以介紹；並進一步針對2010－2011年間美國費城警方與Temple大學安全與犯罪科學中心（簡稱CSCS）合作共同執行的「費城步巡實驗研究」，以及2015年間由英國倫敦學院大學（UCL）與倫敦警方合作，執行名為「犯罪、警務與公民（Crime, Policing and Citizenship）-動態路網時空互動計畫（Space-Time Interactions of Dynamic Networks project）系列研究」等兩項由智能化警務與空間大數據分析觀點出發，整合空間資訊、犯罪科學、電腦科學等學門所執行之研究計畫為典範。再將其研究方法、發現以及結果加以比較與討論，以作為我國警務理論與實務整合上的借鏡。

By using method of documentary reviewing, the study first introduces the background knowledge of using spatial big data analysis to improve the effectiveness of police enforcement; then further analysis two paradigm projects derived from the interdisciplinary perspectives of intelligent policing, spatial big data analysis, spatial information, crime science, computer science, and other disciplines which named ''The Philadelphia Foot Patrol Experiment'' conducted by Philadelphia Police Bureau and CSCS during 2010-2011, and '' Crime, Policing and Citizenship Project- Space-Time Interactions of Dynamic Networks Project'' conducted by UCL and London Police Bureau in 2015. We finally compare and discuss main research methods, findings, and results of the two projects, and hope to serve them as references in both of theory and practice of Policing in our country.