根據警政署統計，臺灣近年來整體犯罪率有下降趨勢，破案率亦逐年提升，但其中最直接影響到治安、居民安全與生活空間的住宅竊盜犯罪案件比例卻居高不下，雖然住宅竊盜罪責較以往提高許多，卻對犯罪者嚇阻效果有限。犯罪者常利用觀察周遭環境而選擇是否作案，若健全的規劃住宅周遭環境，勢必會降低住宅竊盜之發生機率；因此透過環境設計預防犯罪(Crime Prevention Through Environmental Design，CPTED)為都市未來發展之重要指標。許多學者提出預防住宅竊盜之研究，大多由社會人口組成因素、犯罪者心理、環境空間管控等角度著手，或是僅針對建築本身內部之空間規劃，但甚少提及案件發生點位與都市環境間的關聯性。為有效預防犯罪、改善空間構成，並提升生活品質，本研究將透過相關文獻探討分析後，利用臺北市政府開放平台所提供之住宅竊盜案件，配合Google地圖、臺北市政府工務局之地標地圖等資訊，確立住宅竊盜之周邊環境因子與建置資料數據，進行資料探勘之集群與關聯規則統計分析，發現臺北市住宅竊盜犯罪特性多發生在面臨道路寬度為10公尺以上連通道路、住商混合使用型態地區與巷道乾淨未出現臨時停車與植栽過高現象等，最後針對周邊環境特性提出優先改善策略，供警政單位與居民檢視環境之依據，作為未來都市發展可參考或避免之設計典範。

According to the Statistics of Police Administration, the crime rate in Taiwan has declined in recent years, and the detection rate has also increased year by year. However, the proportion of residential burglary that directly affects law and order, residents' safety and living space is still high. Although the crime of residential burglary is higher than before, it has limited effectiveness in deterring criminals. Offenders often observe the surrounding environment to choose the crime target. If the environment is fully planned, it will inevitably reduce the incidence of residential burglary. Therefore, Crime Prevention Through Environmental Design (CPTED) is an important indicator for the future development of the city. Many scholars have proposed research on the prevention of residential burglary, but most of them start from the perspectives of population composition, criminal psychology, environmental space control, or only for architectural space. There is less mention of the connection between the location of the case and the urban environment. To effectively prevent crime, improve the composition of space, and improve the quality of life. This study will explore the relevant literature and use the cases provided by the Taipei City Government's open platform. It also cooperates with Google Maps and the Public Works Department of Taipei City Government to establish the surrounding environmental factors and construction data of residential burglary. Using the Clustering and Associative rules of Data Mining technology. It is found that the characteristics of residential burglary in Taipei City occur mostly in the adjacent roads with a width of 10 meters or more, the mixed residential commercial district and the clean streets. The results will provide the basis for police agencies and residents to examine the environment. As a model of design that can be referenced or avoided in urban development.

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