Discovering Zones Of Different Functions Using Bus Smart Card Data And Points Of Interest

Cities comprise various functional zones, including residential, educational, commercial, industrial zones, etc... It is important for urban planners to identify different functional zones and understand their spatial structure within the city in order to make better urban plans.Micro data is difficult to collect, so classic urban studies are often carried out in the macroscopic scale. In recent years, large-scale, high quality individual space-time data is easier to be obtained due to the rapid development of the LBS (Location Based Service) technology. Using the micro data and data mining technology in the real city urban refinement study has become a main trend of urban studies.In this research, we used77976010bus smart card records of Beijing City in one week in April2008and converted them into two-dimensional time series data of each bus platform, Then, through data mining in the big database system and previous studies on citizens’ trip behavior, we established the DZoF (Discovering Zones of different Functions) model based on SCD (Smart Card Data) and POIs (Points of Interest), and pooled the results at the TAZ (Traffic Analysis Zone) level. The results suggested that DzoF model and cluster analysis based on dimensionality reduction and EM (Expectation-Maximization) algorithm can identify functional zones. The proposed method is demonstrated and verified with real data collected in Beijing. The methodology in the present research can help urban planners and the public understand the complex urban spatial structure and contribute to the academia of urban geography and urban planning.