交通的流動表達了都市活動的差異，其中公共交通扮演重要的角色，完善的公共交通是現代都市發展的要素之一，緣此以大眾運輸場站為導向的都市發展(Transit-Oriented Development, TOD)概念因應產生。公共運輸系統在空間上的分佈狀況以及各運具之間的合理搭配為規劃時的重要資訊，公共自行車則具備了提高公共運輸之及門性與服務範圍的特性，是連接公共交通最後一哩路的關鍵運具。目前臺北市在TOD規劃上鮮有法規與相關規範，現行計畫僅針對步行尺度建立開發許可地區，忽略了公共自行車與捷運的連結以及相關發展手段，缺乏土地使用計畫與管制規範，使得TOD規劃難有所依循。
公共運具間相互連接轉乘的特性用於社會網絡之概念有發展及分析的可能。配合電子票證大數據資料的運用，社會網絡分析能建立站點間互動關係並進行關係集群的判讀，搭配相應之社會網絡指標與空間分析，能判讀TOD之空間範圍，並使各TOD措施與都市空間緊密配合。
以社會網絡觀點討論公共自行車轉乘捷運之互動關係是有其必要性的。本研究以模矩度最佳化分群對轉乘網絡進行分群，以此建立公共自行車尺度之TOD範圍，發現社群多以捷運場站為核心，受到地理因素影響，並具有跨區之現象，亦計算各公共自行車站點的程度中心度，了解不同站點在在轉乘網絡中的重要性。以程度中心度為應變數，藉由地理加權迴歸討論影響各站點之相關變數。藉由前述分析對相關建成環境與政策進行檢討，做為未來TOD相關規劃與公共自行車轉乘提升之參考。

The interaction of transportation expresses the differences in various urban activities, in which public transportation plays an important role, constructing the comprehensive public transportation system is one of the development trends of modern cities, thus the concept of Transit-Oriented Development (TOD) is generated. understanding the spatial distribution of the public transportation system and the reasonable collocation of various vehicles are crucial for planning. Public bicycles can improve the accessibility and the service region of public transportation, it is the key mode of connecting the last mile urban transit. Currently, Taipei has few laws and regulations on TOD planning, the latest plan of TOD only focused on the pedestrian scales development areas, ignoring the interconnection between public bicycle and MRT, and a lack of land use plans and regulations, increasing the difficulty of TOD planning.
It is necessary to discuss the interactive relationship between public bicycles and MRT system from the perspective of social networks. In this study, by using modularity to group the transfer network into clusters. The research found that the communities are mostly centered on the MRT station, which is affected by geographical factors and has a phenomenon of cross-region. By the calculating the degree centrality of each public bicycle station, we can understand the importance of different stations in the transfer network. Taking degree centrality as the dependent variable, we can find out the impact variable from different public bicycle stations by using Geographic Weighted Regression(GWR).
The research results can be used to review the environment and related policies, and serve as a reference for future TOD-related planning and public bicycle transfer promotion.

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