Analyzing Urban Spatial Patterns and Functional Zones Using Sina Weibo POI Data: A Case Study of Beijing

With the development of Web2.0 and mobile Internet, urban residents, a new type “sensor”, provide us with massive amounts volunteered geographic information (VGI). Quantifying spatial patterns VGI plays an increasingly important role in understanding functions. Using social media activity data, this article developed method to automatically extract identify functional zones. The is put forward based on case Beijing, China, includes following three steps: (1) Obtain multi-source such as Weibo data (equivalent Twitter Chinese), OpenStreetMap, population etc.; (2) Use hierarchical clustering algorithm, term frequency-inverse document frequency (TF-IDF) method, improved k-means algorithms zones; (3) Compare identified results actual land uses verify its accuracy. experiment proved that our can effectively zones, ideas for study have great significance optimizing planning.