2009年政府開放資料逐漸興起，台灣也在2012年積極發展開放資料，對於政府開放資料的應用漸漸成為趨勢。另外，以往都市功能性區域分析在蒐集資料都花費不少成本，因此本研究利用開放資源解決資料蒐集成本問題，並針對台北捷運流量資料探討，使得該資料可以應用在都市功能性區域分析上。本文利用階層式分群將捷運站分群，找出大台北地區（涵蓋台北市與新北市）這些捷運站周邊的功能性區域。此外，將分辨出的功能性區域結合商圈開放資料找出商圈與功能性區域的關係，進而了解商圈人潮動向。本研究運用了政府開放資料進行都市與商圈分析並節省資料蒐集成本，針對大眾交通運輸流量在分群前處理時進行探討，最後根據不同功能性區域商圈人潮的特性給予結論。

Government open data gradually become popular since 2009, so as the government of Taiwan. In 2012, the government of Taiwan promoted to open their data. Therefore, the application of using open data become a trend in Taiwan. Moreover, many researchers used much cost to collect data while analyzing functional urban area. So in this paper, we’d like to use government open data to resolve the cost of collecting data and analyze the flow- type data to be applied in functional urban area. Then, we apply agglomerative hierarchical clustering to finish functional urban area identification in Taipei area (including Taipei City and New Taipei City). Besides, we find the relationship between functional urban area and commercial area which collecting from another open data to understand the tendency of people flow. In this paper, we practically utilize government open data to analyze functional urban area and reduce the cost of collecting data; we also discuss the preprocessing while applying flow-type data to cluster the functional urban area. Finally, we get the conclusion according to the different kinds of functional urban area.